diff --git a/.Rbuildignore b/.Rbuildignore index cca6dbe..6d83887 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -5,3 +5,6 @@ ^LICENSE\.md$ ^codecov\.yml$ ^docs +^_pkgdown\.yml$ +^docs$ +^pkgdown$ diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index dcc7d0a..df033da 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -1,15 +1,10 @@ -# For help debugging build failures open an issue on the RStudio community with the 'github-actions' tag. -# https://community.rstudio.com/new-topic?category=Package%20development&tags=github-actions +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help on: push: - branches: - - main - - master - - devel + branches: [main, master, devel] pull_request: - branches: - - main - - master + branches: [main, master] name: R-CMD-check @@ -23,71 +18,37 @@ jobs: fail-fast: false matrix: config: + #- {os: macos-latest, r: 'release'} - {os: windows-latest, r: 'release'} - - {os: macOS-latest, r: 'release'} - - {os: ubuntu-20.04, r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - - {os: ubuntu-20.04, r: 'devel', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'} + - {os: ubuntu-latest, r: 'release'} + - {os: ubuntu-latest, r: 'oldrel-1'} env: - R_REMOTES_NO_ERRORS_FROM_WARNINGS: true - RSPM: ${{ matrix.config.rspm }} + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + R_KEEP_PKG_SOURCE: yes steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v3 - - uses: r-lib/actions/setup-r@v1 - with: - r-version: ${{ matrix.config.r }} - - - uses: r-lib/actions/setup-pandoc@v1 - - - name: Query dependencies - run: | - install.packages('remotes') - saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2) - writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version") - shell: Rscript {0} + - uses: r-lib/actions/setup-pandoc@v2 - - name: Cache R packages - if: runner.os != 'Windows' - uses: actions/cache@v2 + - uses: r-lib/actions/setup-r@v2 with: - path: ${{ env.R_LIBS_USER }} - key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }} - restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1- - - - name: Install system dependencies + r-version: ${{ matrix.config.r }} + http-user-agent: ${{ matrix.config.http-user-agent }} + use-public-rspm: true + + - name: Install Linux system dependencies if: runner.os == 'Linux' run: | - while read -r cmd - do - eval sudo $cmd - done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))') - sudo apt-get install -y libopenbabel-dev + sudo apt install libopenbabel-dev libeigen3-dev - - name: Install dependencies - run: | - remotes::install_deps(dependencies = TRUE) - remotes::install_cran(c("rcmdcheck","goodpractice")) - shell: Rscript {0} - - - name: Check - env: - _R_CHECK_CRAN_INCOMING_REMOTE_: false - run: rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran"), error_on = "warning", check_dir = "check") - shell: Rscript {0} + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::rcmdcheck + needs: check - - name: Goodpractice - run: goodpractice::goodpractice() - shell: Rscript {0} - - - name: Test coverage - run: covr::codecov() - shell: Rscript {0} - - - name: Upload check results - if: failure() - uses: actions/upload-artifact@main + - uses: r-lib/actions/check-r-package@v2 with: - name: ${{ runner.os }}-r${{ matrix.config.r }}-results - path: check + upload-snapshots: true diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml new file mode 100644 index 0000000..a1acda1 --- /dev/null +++ b/.github/workflows/pkgdown.yaml @@ -0,0 +1,51 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + release: + types: [published] + workflow_dispatch: + +name: pkgdown + +jobs: + pkgdown: + runs-on: ubuntu-latest + # Only restrict concurrency for non-PR jobs + concurrency: + group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }} + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + steps: + - uses: actions/checkout@v3 + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Install Linux system dependencies + if: runner.os == 'Linux' + run: | + sudo apt install libopenbabel-dev libeigen3-dev + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + - name: Build site + run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE) + shell: Rscript {0} + + - name: Deploy to GitHub pages 🚀 + if: github.event_name != 'pull_request' + uses: JamesIves/github-pages-deploy-action@v4.4.1 + with: + clean: false + branch: gh-pages + folder: docs diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml new file mode 100644 index 0000000..c4f0b3a --- /dev/null +++ b/.github/workflows/test-coverage.yaml @@ -0,0 +1,55 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + +name: test-coverage + +jobs: + test-coverage: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + + steps: + - uses: actions/checkout@v3 + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Install Linux system dependencies + if: runner.os == 'Linux' + run: | + sudo apt install libopenbabel-dev libeigen3-dev + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::covr + needs: coverage + + - name: Test coverage + run: | + covr::codecov( + quiet = FALSE, + clean = FALSE, + install_path = file.path(Sys.getenv("RUNNER_TEMP"), "package") + ) + shell: Rscript {0} + + - name: Show testthat output + if: always() + run: | + ## -------------------------------------------------------------------- + find ${{ runner.temp }}/package -name 'testthat.Rout*' -exec cat '{}' \; || true + shell: bash + + - name: Upload test results + if: failure() + uses: actions/upload-artifact@v3 + with: + name: coverage-test-failures + path: ${{ runner.temp }}/package diff --git a/.gitignore b/.gitignore index 5b6a065..234f028 100644 --- a/.gitignore +++ b/.gitignore @@ -2,3 +2,4 @@ .Rhistory .RData .Ruserdata +docs diff --git a/DESCRIPTION b/DESCRIPTION index e690103..e94d84a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,46 +1,46 @@ Package: riches Title: Strucutral and Functional Enrichment Analyses -Version: 0.2.1 +Version: 0.3.0 Authors@R: person(given = "Jasen", family = "Finch", role = c("aut", "cre"), email = "jsf9@aber.ac.uk") -Description: Structural and functional enrichment for metabolomics data. +Description: Structural and functional enrichment for metabolomics data. URL: https://jasenfinch.github.io/riches/ BugReports: https://github.com/jasenfinch/riches/issues biocViews: Metabolomics License: GPL-3 Encoding: UTF-8 +Roxygen: list(markdown = TRUE) Depends: R (>= 3.5.0) -Imports: FELLA, - MFassign, +Imports: + broom, + cheminf, + construction, dplyr, - ggthemes, + FELLA, + igraph, magrittr, - stringr, - tidygraph, + metabolyseR, methods, mzAnnotation, purrr, - metabolyseR, - ggplot2, - ggraph, - tibble -Remotes: jasenfinch/MFassign, - jasenfinch/mzAnnotation, - jasenfinch/metabolyseR + rlang, + stringr, + tibble, + tidygraph, + tidyr, + tidyselect +Remotes: aberHRML/assignments, + aberHRML/mzAnnotation, + jasenfinch/cheminf, + jasenfinch/construction, + jasenfinch/metabolyseR, + bioc::FELLA LazyData: true -RoxygenNote: 7.1.1 -Collate: allClasses.R - allGenerics.R - access.R - enrichmentParameters.R - example-data.R - functionalEnrichment.R - organismNetwork.R - plotGraph.R - riches.R +RoxygenNote: 7.2.3 Suggests: + assignments, testthat, covr diff --git a/NAMESPACE b/NAMESPACE index cf12e95..7463ecd 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,53 +1,84 @@ # Generated by roxygen2: do not edit by hand -export(enrichmentParameters) -export(organismNetwork) -exportMethods("functional<-") -exportMethods(functional) -exportMethods(functionalEnrichment) +export("%>%") +export(availableMethods) +export(enrichmentResults) +export(functionalEnrichment) +export(generateResultsTable) +export(hits) +export(organismData) +export(structuralClassifications) +export(structuralEnrichment) +exportMethods(explanatoryFeatures) importFrom(FELLA,buildDataFromGraph) importFrom(FELLA,buildGraphFromKEGGREST) importFrom(FELLA,defineCompounds) -importFrom(FELLA,generateResultsGraph) +importFrom(FELLA,generateResultsTable) importFrom(FELLA,getGraph) -importFrom(FELLA,listInternalDatabases) importFrom(FELLA,loadKEGGdata) importFrom(FELLA,runDiffusion) importFrom(FELLA,runHypergeom) importFrom(FELLA,runPagerank) -importFrom(MFassign,assignments) -importFrom(MFassign,nodes) +importFrom(broom,tidy) +importFrom(cheminf,descriptors) +importFrom(cheminf,entries) +importFrom(cheminf,filterEntries) +importFrom(cheminf,filterIP) +importFrom(cheminf,filterMF) +importFrom(cheminf,metaboliteDB) +importFrom(construction,classifications) +importFrom(dplyr,across) +importFrom(dplyr,all_of) +importFrom(dplyr,any_of) +importFrom(dplyr,arrange) +importFrom(dplyr,bind_cols) importFrom(dplyr,bind_rows) +importFrom(dplyr,count) importFrom(dplyr,distinct) +importFrom(dplyr,everything) importFrom(dplyr,filter) +importFrom(dplyr,group_by) +importFrom(dplyr,group_keys) +importFrom(dplyr,group_map) +importFrom(dplyr,inner_join) +importFrom(dplyr,left_join) importFrom(dplyr,mutate) +importFrom(dplyr,relocate) +importFrom(dplyr,rename) +importFrom(dplyr,rowwise) importFrom(dplyr,select) -importFrom(ggplot2,aes) -importFrom(ggplot2,coord_fixed) -importFrom(ggplot2,labs) -importFrom(ggplot2,scale_colour_manual) -importFrom(ggraph,create_layout) -importFrom(ggraph,geom_edge_link) -importFrom(ggraph,geom_node_point) -importFrom(ggraph,geom_node_text) -importFrom(ggraph,ggraph) -importFrom(ggraph,theme_graph) -importFrom(ggthemes,ptol_pal) +importFrom(dplyr,summarise) +importFrom(dplyr,ungroup) +importFrom(igraph,vertex.attributes) importFrom(magrittr,"%>%") importFrom(magrittr,set_names) importFrom(metabolyseR,analysisResults) +importFrom(metabolyseR,dat) importFrom(metabolyseR,explanatoryFeatures) +importFrom(metabolyseR,features) +importFrom(metabolyseR,keepFeatures) +importFrom(metabolyseR,nFeatures) +importFrom(metabolyseR,sinfo) +importFrom(metabolyseR,type) +importFrom(methods,as) importFrom(methods,new) -importFrom(mzAnnotation,descriptors) -importFrom(mzAnnotation,filterACCESSIONS) -importFrom(mzAnnotation,filterIP) -importFrom(mzAnnotation,filterMF) -importFrom(mzAnnotation,getAccessions) -importFrom(mzAnnotation,metaboliteDB) +importFrom(methods,show) +importFrom(mzAnnotation,adduct_rules) importFrom(purrr,map) -importFrom(stringr,coll) -importFrom(stringr,str_c) -importFrom(stringr,str_split_fixed) +importFrom(purrr,map_chr) +importFrom(rlang,parse_expr) +importFrom(rlang,sym) +importFrom(stats,cor) +importFrom(stats,fisher.test) +importFrom(stats,median) +importFrom(stats,p.adjust) +importFrom(stringr,str_extract_all) +importFrom(tibble,as_tibble) importFrom(tibble,tibble) importFrom(tidygraph,activate) importFrom(tidygraph,as_tbl_graph) +importFrom(tidyr,drop_na) +importFrom(tidyr,gather) +importFrom(tidyr,separate) +importFrom(tidyr,spread) +importFrom(tidyselect,last_col) diff --git a/NEWS.md b/NEWS.md new file mode 100644 index 0000000..4642d86 --- /dev/null +++ b/NEWS.md @@ -0,0 +1,21 @@ +# riches 0.3.0 + +* Added a `NEWS.md` file to track changes to the package. + +* Replaced the example data set with a molecular formula assigned [`AnalysisData`](https://jasenfinch.github.io/metabolyseR/reference/AnalysisData-class.html) class object. + +* Added a `functionalEnrichment()` method for the [`RandomForest`](https://jasenfinch.github.io/metabolyseR/reference/RandomForest-class.html) S4 class. + +* Removed the `EnrichmentParameters` S4 class and associated methods. + +* Added example organism [FELLA](https://bioconductor.org/packages/release/bioc/html/FELLA.html) data for *Brachypodium distachyon* (`bdi`). + +* Added the `organismData()` function as a convenience wrapper for loading and building KEGG graph data for [FELLA](https://bioconductor.org/packages/release/bioc/html/FELLA.html) enrichment analyses. + +* Added accessor methods for the `FunctionalEnrichment` S4 class. + +* Added example structural classifications. + +* Added the `structuralEnrichment()` method for the [`RandomForest`](https://jasenfinch.github.io/metabolyseR/reference/RandomForest-class.html) S4 class. + +* Functional and structural enrichment analyses can now be performed on explanatory features split by feature trends for binary comparisons or regression using the `split` argument of `functionEnrichment()` and `structuralEnrichment()`. diff --git a/R/access.R b/R/access.R deleted file mode 100644 index 68db8fd..0000000 --- a/R/access.R +++ /dev/null @@ -1,29 +0,0 @@ - -setMethod('availablePairwises',signature = 'FunctionalEnrichment', - function(x){ - x@explanatory %>% - .$Pairwise %>% - unique() - } -) - -#' Get and set enrichment parameters -#' @rdname EnrichmentParameters-accessors -#' @description Retrieve or set enrichment parameters. -#' @param x S4 object of class EnrichmentParameters -#' @param value value to set -#' @export - -setMethod('functional',signature = 'EnrichmentParameters', - function(x){ - x@functional - }) - -#' @rdname EnrichmentParameters-accessors -#' @export - -setMethod('functional<-',signature = 'EnrichmentParameters', - function(x,value){ - x@functional <- value - return(x) - }) \ No newline at end of file diff --git a/R/allClasses.R b/R/allClasses.R deleted file mode 100644 index acfc698..0000000 --- a/R/allClasses.R +++ /dev/null @@ -1,33 +0,0 @@ - -setClass('EnrichmentParameters', - slots = list( - organism = 'character', - features = 'list', - functional = 'list', - structural = 'list' - ), - prototype = list( - functional = list(methods = c('hypergeom', - 'diffusion', - 'pagerank')) - ) -) - -setClass('FunctionalEnrichment', - slots = list( - network = 'FELLA.DATA', - hits = 'tbl_df', - explanatory = 'tbl_df', - results = 'list' - ) -) - -setClass('StructuralEnrichment') - -# setClass('Enrichment', -# slots = list( -# workflow = 'Workflow', -# functional = 'FunctionalEnrichment', -# structural = 'StructuralEnrichment' -# ) -# ) \ No newline at end of file diff --git a/R/allGenerics.R b/R/allGenerics.R deleted file mode 100644 index 89eb4b3..0000000 --- a/R/allGenerics.R +++ /dev/null @@ -1,30 +0,0 @@ - -setGeneric('organismCompounds',function(FELLA){ - standardGeneric('organismCompounds') -}) - -#' @rdname functionalEnrichment -setGeneric('functionalEnrichment',function(analysis,assignment,parameters){ - standardGeneric('functionalEnrichment') -}) - - -setGeneric('plotGraph',function(x,comparison,type = 'diffusion'){ - standardGeneric('plotGraph') -}) - -setGeneric('availablePairwises',function(x){ - standardGeneric('availablePairwises') -}) - -#' @rdname EnrichmentParameters-accessors - -setGeneric('functional',function(x){ - standardGeneric('functional') -}) - -#' @rdname EnrichmentParameters-accessors - -setGeneric('functional<-',function(x,value){ - standardGeneric('functional<-') -}) \ No newline at end of file diff --git a/R/assigned-data.R b/R/assigned-data.R new file mode 100644 index 0000000..418f475 --- /dev/null +++ b/R/assigned-data.R @@ -0,0 +1,8 @@ +#' Example analysis data +#' @format S4 object of class AnalysisData from the metabolyseR package. +#' @source Example analysis data based on the *Brachypodium distachyon* +#' ecotype comparison FIE-MS metabolomic fingerprinting data set available +#' in the metaboData package. The features include putative molecular formula +#' assignments. + +"assigned_data" diff --git a/R/enrichmentParameters.R b/R/enrichmentParameters.R deleted file mode 100644 index 37f6cc8..0000000 --- a/R/enrichmentParameters.R +++ /dev/null @@ -1,20 +0,0 @@ -#' enrichmentParameters -#' @description Enrichment parameters. -#' @param organism KEGG organism ID -#' @param model model type to use for extracting explanatory features -#' @param response response variable name to use for extracting explanatory features -#' @param threshold explanatory feature cutoff -#' @importFrom methods new -#' @export - -enrichmentParameters <- function(organism, model = 'randomForest', response = 'class', threshold = 0.05){ - new('EnrichmentParameters', - organism = organism, - features = list( - model = model, - response = response, - threshold = threshold - ), - structural = list() - ) -} \ No newline at end of file diff --git a/R/example-data.R b/R/example-data.R deleted file mode 100644 index fa5441e..0000000 --- a/R/example-data.R +++ /dev/null @@ -1,15 +0,0 @@ -#' Example analysis data -#' @format S4 object of class Analysis from the metabolyseR package. -#' @source Example analysis data based on the Brachypodium distachyon -#' ecotype comparison FIE-MS metabolomic fingerprinting data set available -#' in the metaboData package. - -"example_analysis" - -#' Example molecular formula assignment data -#' @format S4 object of class Assignment from the MFassign package. -#' @source Example analysis data based on the Brachypodium distachyon -#' ecotype comparison FIE-MS metabolomic fingerprinting data set available -#' in the metaboData package. - -"example_assignment" \ No newline at end of file diff --git a/R/functional-enrichment.R b/R/functional-enrichment.R new file mode 100644 index 0000000..e43dbeb --- /dev/null +++ b/R/functional-enrichment.R @@ -0,0 +1,372 @@ +#' Available functional enrichment methods +#' @description Methods available for functional enrichment using the FELLA package +#' @return A character vector of available methods. +#' @examples +#' availableMethods() +#' @export + +availableMethods <- function(){ + c('hypergeom','diffusion','pagerank') +} + +setClass('FunctionalEnrichment', + slots = list( + organism_data = 'FELLA.DATA', + hits = 'tbl_df', + explanatory = 'tbl_df', + results = 'list' + ), + contains = c('RandomForest', + 'FELLA.DATA') +) + +#' @importFrom methods as show + +setMethod('show',signature = 'FunctionalEnrichment', + function(object){ + show(as(object,'RandomForest')) + show(as(object,'FELLA.DATA')) + message() + cat(length(unique(hits(object)$feature)),'m/z features matched to KEGG compounds.\n') + cat(length(unique(explanatoryFeatures(object)$feature)),'explanatory m/z features.') + message() + + purrr::iwalk(enrichmentResults(object), + ~{ + message() + cat(.y,'\n') + show(.x) + }) + }) + +#' FunctionalEnrichment S4 class accessors +#' @rdname functional-accessors +#' @description Accessor methods for the `FunctionalEnrichment` S4 class. +#' @param x object of S4 class `FunctionalEnrichment` +#' @param method the method results to access. One of `availableMethods`. +#' @param nlimit argument to pass to argument `nlimit` of `FELLA::generateResultsTable`. Limits the order of the sub-graph solutions for methods `diffusion` and `pagerank`. +#' @param ... ignored +#' @return A tibble or a list of objects of `FELLA.USER` S4 class depending on the method used. +#' @examples +#' ## Perform random forest on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class' +#' ) +#' +#' ## Perform functional enrichment analysis +#' enrichment_results <- functionalEnrichment( +#' random_forest, +#' 'bdi', +#' methods = 'hypergeom', +#' organism_data = organismData( +#' 'bdi', +#' database_directory = system.file( +#' 'bdi', +#' package = 'riches'), +#' internal_directory = FALSE +#' ) +#' ) +#' +#' ## Access the m/z feature KEGG compound matches +#' hits(enrichment_results) +#' +#' ## Access the explanatory features used for functional enrichment +#' explanatoryFeatures(enrichment_results) +#' +#' ## Access the FELLA.USER functional enrichment object +#' enrichmentResults(enrichment_results) +#' +#' ## Extract a table of enrichment results +#' generateResultsTable(enrichment_results) +#' @export + +setGeneric('hits',function(x) + standardGeneric('hits') +) + +#' @rdname functional-accessors + +setMethod('hits',signature = 'FunctionalEnrichment', + function(x){ + x@hits + }) + +#' @rdname functional-accessors +#' @export + +setMethod('explanatoryFeatures',signature = 'FunctionalEnrichment', + function(x){ + x@explanatory + }) + +#' @rdname functional-accessors +#' @export + +setGeneric('enrichmentResults',function(x) + standardGeneric('enrichmentResults') +) + +#' @rdname functional-accessors + +setMethod('enrichmentResults',signature = 'FunctionalEnrichment', + function(x){ + x@results + }) + +#' @rdname functional-accessors +#' @export + +setGeneric('generateResultsTable',function( + x, + method = availableMethods(), + nlimit = 250, + ...) + standardGeneric('generateResultsTable') +) + +#' @rdname functional-accessors +#' @importFrom FELLA generateResultsTable + +setMethod('generateResultsTable',signature = 'FunctionalEnrichment', + function(x, + method = availableMethods(), + nlimit = 250){ + + method <- match.arg( + method, + choices = availableMethods() + ) + + x %>% + enrichmentResults() %>% + map(~{ + if (!is.null(.x)){ + FELLA::generateResultsTable( + method = method, + nlimit = nlimit, + LabelLengthAtPlot = 50, + object = .x, + data = x + ) %>% + tibble::as_tibble() + } + }) %>% + bind_rows(.id = 'comparison') + }) + +#' Functional enrichment +#' @rdname functionalEnrichment +#' @description Perform functional enrichment analyses of explanatory features using the +#' [{FELLA}](https://bioconductor.org/packages/release/bioc/html/FELLA.html) R package. +#' @param x object of S4 class `RandomForest` +#' @param organism the KEGG code for the organism of interest +#' @param methods the enrichment techniques to build. Any returned by `availableMethods`. +#' @param split split the explanatory features into further groups based on their trends. See details. +#' @param organism_data an object of S4 class `FELLA.DATA` +#' @param adduct_rules_table the adduct ionisation rules for matching m/z features to KEGG compounds. +#' Format should be as returned from `mzAnnotation::adduct_rules`. +#' @param ... arguments to pass to `metabolyseR::explanatoryFeatures` +#' @details +#' For argument `split = 'trends'`, the explanatory features can be split into further groups +#' based on their trends. This is not supported for unsupervised random forest. +#' +#' For random forest classification, this is for binary comparisons only. Functional enrichment +#' is performed seperately on the up and down regulated explanatory features for each comparison. The +#' `up regulated` and `down regulated` groups are based on the trends of log2 ratios between +#' the comparison classes. `up regulated` explanatory features have a higher median intensity +#' in the right-hand class compared to the left-hand class of the comparison. The opposite is true +#' for the `down regulated` explanatory features. +#' +#' For random forest regression, the explanatory features are split based on their Spearman's +#' correlation coefficient with the response variable prior to functional enrichment analysis +#' giving `positively correlated` and `negatively correlated` subgroups. +#' @return An object of S4 class `FunctionalEnrichment`. +#' @examples +#' ## Perform random forest on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class' +#' ) +#' +#' ## Perform functional enrichment analysis +#' functionalEnrichment( +#' random_forest, +#' 'bdi', +#' methods = 'hypergeom', +#' organism_data = organismData( +#' 'bdi', +#' database_directory = system.file( +#' 'bdi', +#' package = 'riches'), +#' internal_directory = FALSE +#' ) +#' ) +#' +#' ## An example using split trends +#' ## Perform binary random forest classification on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class', +#' binary = TRUE +#' ) +#' +#' ## Perform functional enrichment analysis +#' functionalEnrichment( +#' random_forest, +#' 'bdi', +#' methods = 'hypergeom', +#' split = 'trends', +#' organism_data = organismData( +#' 'bdi', +#' database_directory = system.file( +#' 'bdi', +#' package = 'riches'), +#' internal_directory = FALSE +#' ) +#' ) +#' @importFrom FELLA defineCompounds runHypergeom runDiffusion runPagerank +#' @importFrom cheminf metaboliteDB descriptors filterEntries filterMF filterIP entries +#' @importFrom dplyr select distinct bind_rows group_keys +#' @importFrom purrr map +#' @importFrom metabolyseR analysisResults explanatoryFeatures type +#' @importFrom magrittr set_names +#' @importFrom mzAnnotation adduct_rules +#' @importFrom methods new +#' @export + +setGeneric('functionalEnrichment',function(x, + organism, + methods = availableMethods(), + split = c('none','trends'), + organism_data = organismData(organism), + adduct_rules_table = adduct_rules(), + ...) + standardGeneric('functionalEnrichment') +) + +#' @rdname functionalEnrichment + +setMethod( + 'functionalEnrichment', + signature = 'RandomForest', + function( + x, + organism, + methods = availableMethods(), + split = c('none','trends'), + organism_data = organismData(organism), + adduct_rules_table = adduct_rules(), + ... + ){ + + rf_type <- type(x) + + methods <- match.arg(methods, + choices = availableMethods(), + several.ok = TRUE) + + split <- match.arg(split, + choices = c( + 'none', + 'trends' + )) + + explanatory_features <- explanatoryFeatures(x,...) + + if (split == 'trends'){ + explanatory_features <- trends(x,explanatory_features) + } + + mf_hits <- pips(x, + organism_data, + adduct_rules_table) + + background_compounds <- mf_hits$ID %>% + unique() + + if (rf_type == 'classification'){ + explanatory_features <- explanatory_features %>% + group_by(response,comparison) + } + + if (rf_type == 'regression'){ + explanatory_features <- explanatory_features %>% + group_by(response) + } + + if (split == 'trends'){ + explanatory_features <- explanatory_features %>% + group_by(trend,.add = TRUE) + } + + enrichment_results <- explanatory_features %>% + dplyr::group_map(~{ + message() + + if (rf_type != 'unsupervised'){ + message(.x$response[1]) + } + + if (rf_type == 'classification'){ + message(.x$comparison[1]) + } + + if (split == 'trends'){ + message(.x$trend[1]) + } + + explanatory_compounds <- mf_hits %>% + filter(name %in% .x$feature) %>% + .$ID %>% + unique() + + if (length(explanatory_compounds) > 0) { + comparison_enrichment <- defineCompounds( + compounds = explanatory_compounds, + compoundsBackground = background_compounds, + data = organism_data) + + if ('hypergeom' %in% methods) { + comparison_enrichment <- comparison_enrichment %>% + runHypergeom(data = organism_data) + } + + if ('diffusion' %in% methods) { + comparison_enrichment <- comparison_enrichment %>% + runDiffusion(data = organism_data) + } + + if ('pagerank'%in% methods) { + comparison_enrichment <- comparison_enrichment %>% + runPagerank(data = organism_data) + } + + return(comparison_enrichment) + } else { + message('No assigned explanatory m/z features matched to KEGG compounds.') + } + },.keep = TRUE) + + + if (rf_type != 'unsupervised') { + group_names <- group_keys(explanatory_features) %>% + tidyr::unite(name) %>% + .$name + + enrichment_results <- enrichment_results %>% + set_names(group_names) + } + + + results <- new( + 'FunctionalEnrichment', + x, + organism_data, + hits = mf_hits, + explanatory = explanatory_features, + results = enrichment_results + ) + + return(results) + }) diff --git a/R/functionalEnrichment.R b/R/functionalEnrichment.R deleted file mode 100644 index bf3f75b..0000000 --- a/R/functionalEnrichment.R +++ /dev/null @@ -1,115 +0,0 @@ -#' functionalEnrichment -#' @rdname functionalEnrichment -#' @description Functional enrichment. -#' @param analysis S4 object of class Analysis -#' @param assignment S4 object of class Assignment -#' @param parameters S4 object of class EnrichmentParameters -#' @examples -#' \dontrun{ -#' ## Generate enrichment parameters -#' parameters <- enrichmentParameters('bdi') -#' -#' ## Select only "diffusion" enrichment -#' functional(parameters) <- list(methods = 'diffusion') -#' -#' ## Run functional enrichment -#' fe <- functionalEnrichment(example_analysis,example_assignment,parameters) -#' } -#' @importFrom FELLA defineCompounds runHypergeom runDiffusion runPagerank -#' @importFrom mzAnnotation metaboliteDB descriptors filterACCESSIONS filterMF filterIP getAccessions -#' @importFrom MFassign assignments -#' @importFrom dplyr select distinct bind_rows -#' @importFrom purrr map -#' @importFrom metabolyseR analysisResults explanatoryFeatures -#' @importFrom magrittr set_names -#' @export - -setMethod('functionalEnrichment',signature = signature(analysis = 'Analysis',assignment = 'Assignment',parameters = 'EnrichmentParameters'), - function(analysis,assignment,parameters){ - - FELLA <- organismNetwork(parameters@organism) - - adductRules <- assignment %>% - .@parameters %>% - .@adductRules - - oc <- organismCompounds(FELLA) - - oc <- metabolites %>% - filterACCESSIONS(oc$name) - - mfs <- assignment %>% - assignments() %>% - select(Name,MF,Adduct) %>% - distinct() - - MFhits <- mfs %>% - split(1:nrow(.)) %>% - map(~{ - m <- . - oc %>% - filterMF(m$MF) %>% - filterIP(adductRules$Rule[adductRules$Name == m$Adduct]) %>% - getAccessions() %>% - mutate(Name = m$Name,MF = m$MF,Adduct = m$Adduct) - }) %>% - bind_rows() - - bc <- MFhits$ID %>% - unique() - - explanFeat <- analysis %>% - analysisResults('modelling') %>% - .[[parameters@features$model]] %>% - explanatoryFeatures(threshold = parameters@features$threshold) %>% - filter(Response == parameters@features$response) - - comparisons <- explanFeat$Comparison %>% - unique() - - enrichRes <- comparisons %>% - map(~{ - p <- . - message(str_c('\n',p)) - feat <- explanFeat %>% - filter(Comparison == p) - ec <- MFhits %>% - filter(Name %in% feat$Feature) %>% - .$ID %>% - unique() - if (length(ec) > 0) { - comp <- defineCompounds( - compounds = ec, - compoundsBackground = bc, - data = FELLA) - - if ('hypergeom' %in% functional(parameters)$methods) { - comp <- comp %>% - runHypergeom(data = FELLA) - } - - if ('diffusion' %in% functional(parameters)$methods) { - comp <- comp %>% - runDiffusion(data = FELLA) - } - - if ('pagerank'%in% functional(parameters)$methods) { - comp <- comp %>% - runPagerank(data = FELLA) - } - - return(comp) - } else { - message('No explanatory features assigned.') - } - }) %>% - set_names(comparisons) - - new('FunctionalEnrichment', - network = FELLA, - hits = MFhits, - explanatory = explanFeat, - results = enrichRes - ) - } -) \ No newline at end of file diff --git a/R/organism-data.R b/R/organism-data.R new file mode 100644 index 0000000..28bd7ed --- /dev/null +++ b/R/organism-data.R @@ -0,0 +1,113 @@ +#' @importFrom FELLA buildGraphFromKEGGREST buildDataFromGraph + +buildGraph <- function(organism, + methods = availableMethods(), + filter_path = NULL, + database_directory = NULL, + internal_directory = TRUE, + damping_factor = 0.85, + niter = 100){ + + organism_graph <- buildGraphFromKEGGREST( + organism = organism, + filter.path = filter_path) + + buildDataFromGraph( + keggdata.graph = organism_graph, + databaseDir = database_directory, + internalDir = internal_directory, + matrices = methods, + normality = c("diffusion", "pagerank"), + dampingFactor = damping_factor, + niter = niter) +} + +#' Organism data +#' @description Load or build the organism specific KEGG datafor enrichment analysis. +#' This provides a convenience wrapper around `FELLA::loadKEGGdata`, `FELLA::buildGraphFromKEGGREST` and +#' `FELLA::buildDataFromGraph`. See the documentation of these functions for further information. +#' @param organism the KEGG code for the organism of interest +#' @param methods the enrichment techniques to build. Any returned by `availableMethods`. +#' @param filter_path argument to pass to argument `filter.path` of `FELLA::buildGraphFromKEGGREST`. A vector of regular expressions to match pathways to exclude. +#' @param database_directory argument to pass to argument `databaseDir` of `FELLA::buildDataFromGraph` and `FELLA::loadKEGGdata`. The directory name/path in which to save the KEGG data. +#' @param internal_directory logical. Argument to pass to argument `internalDir` of `FELLA::buildDataFromGraph` and `FELLA::loadKEGGdata`. Should the save directory be internal to the FELLA package directory? +#' @param damping_factor argument to pass to argument `dampingFactor` of `FELLA::buildDataFromGraph`. A value between 0 and 1 for the PageRank damping factor. +#' @param niter argument to pass to argument `niter` of `FELLA::buildDataFromGraph`. A value between 10 and 1000. The number of iterations to estimate the values for CC size. +#' @return An object of S4 class `FELLA.DATA` containing the KEGG data for the specified organism. +#' @examples +#' ## Load the example organism data available from within the package +#' organismData( +#' 'bdi', +#' database_directory = system.file( +#' 'bdi', +#' package = 'riches'), +#' internal_directory = FALSE +#' ) +#' @importFrom FELLA loadKEGGdata +#' @export + +organismData <- function(organism, + methods = availableMethods(), + filter_path = NULL, + database_directory = organism, + internal_directory = TRUE, + damping_factor = 0.85, + niter = 100){ + + organism_graph <- try( + loadKEGGdata( + databaseDir = database_directory, + internalDir = internal_directory, + loadMatrix = c('diffusion','pagerank')), + silent = TRUE + ) + + if (inherits(organism_graph,'try-error')){ + message('KEGG data not found. Building...') + + buildGraph(organism, + methods = methods, + filter_path = filter_path, + database_directory = database_directory, + internal_directory = internal_directory, + damping_factor = damping_factor, + niter = niter) + + organism_graph <- loadKEGGdata( + databaseDir = database_directory, + internalDir = internal_directory, + loadMatrix = methods[methods != 'hypergeom']) + } + + return(organism_graph) +} + +setGeneric('organismCompounds',function(organism_data){ + standardGeneric('organismCompounds') +}) + +#' @importFrom magrittr %>% +#' @importFrom tidygraph as_tbl_graph +#' @importFrom FELLA getGraph +#' @importFrom dplyr filter +#' @importFrom igraph vertex.attributes +#' @importFrom tibble as_tibble +#' @importFrom purrr map_chr +#' @importFrom tidygraph as_tbl_graph activate + +setMethod('organismCompounds',signature = 'FELLA.DATA', + function(organism_data){ + organism_data %>% + getGraph() %>% + as_tbl_graph() %>% + activate(nodes) %>% + filter(com == 5) %>% + select(name,NAME) %>% + vertex.attributes() %>% + as_tibble() %>% + mutate( + NAME = map_chr(NAME,~.x[[1]]) + ) + } +) + diff --git a/R/organismNetwork.R b/R/organismNetwork.R deleted file mode 100644 index 2c2140e..0000000 --- a/R/organismNetwork.R +++ /dev/null @@ -1,48 +0,0 @@ -#' organismNetwork -#' @description Gather organism specific KEGG network ready for enrichment analysis -#' @param organism KEGG organism code -#' @importFrom FELLA buildGraphFromKEGGREST buildDataFromGraph loadKEGGdata listInternalDatabases -#' @importFrom stringr str_c -#' @export - -organismNetwork <- function(organism = 'hsa'){ - - if (!(organism %in% listInternalDatabases())) { - message('Internal database not found for this organism. Building...') - - g <- buildGraphFromKEGGREST(organism = organism, filter.path = NULL) - - buildDataFromGraph( - keggdata.graph = g, - databaseDir = organism, - internalDir = TRUE, - matrices = c("hypergeom", "diffusion", "pagerank"), - normality = c("diffusion", "pagerank"), - dampingFactor = 0.85, - niter = 1e3) - } - - FELLA.DATA <- loadKEGGdata( - organism, - internalDir = TRUE, - loadMatrix = c('diffusion','pagerank')) - - return(FELLA.DATA) -} - -#' @importFrom magrittr %>% -#' @importFrom tidygraph as_tbl_graph -#' @importFrom FELLA getGraph -#' @importFrom MFassign nodes -#' @importFrom dplyr filter - -setMethod('organismCompounds',signature = 'FELLA.DATA', - function(FELLA){ - FELLA %>% - getGraph() %>% - as_tbl_graph() %>% - nodes() %>% - filter(com == 5) - } -) - diff --git a/R/pips.R b/R/pips.R new file mode 100644 index 0000000..6bc93b5 --- /dev/null +++ b/R/pips.R @@ -0,0 +1,60 @@ + +#' @importFrom metabolyseR features +#' @importFrom tidyr separate +#' @importFrom dplyr across everything +#' @importFrom tibble tibble + +extractAssignments <- function(x){ + feature_assignments <- tibble( + name = features(x) + ) %>% + separate( + name, + c('feature','MF','isotope','adduct'), + sep = ' ', + fill = 'right', + remove = FALSE + ) %>% + mutate(across( + .cols = everything(), + .fns = ~replace(.x, + .x == "", + NA) + )) +} + +#' @importFrom rlang parse_expr +#' @importFrom dplyr left_join rename + +pips <- function(x,organism_data,adduct_rules_table){ + organism_compounds <- organismCompounds(organism_data) + + organism_database <- metabolites %>% + filterEntries(organism_compounds$name) + + feature_assignments <- x %>% + extractAssignments() %>% + filter(!is.na(MF)) + + mf_hits <- feature_assignments %>% + dplyr::rowwise() %>% + dplyr::group_map(~{ + adduct_rule <- adduct_rules_table %>% + filter(Name == .x$adduct) %>% + .$Rule %>% + parse_expr() + + organism_database %>% + filterMF(.x$MF) %>% + filterIP(rule = !!adduct_rule) %>% + entries() %>% + mutate(name = .x$name, + feature = .x$feature, + adduct = .x$adduct) + }) %>% + bind_rows() %>% + left_join(organism_compounds %>% + rename(ID = name, + compound = NAME), + by = 'ID') +} diff --git a/R/plot.R b/R/plot.R new file mode 100644 index 0000000..9a2fb02 --- /dev/null +++ b/R/plot.R @@ -0,0 +1,62 @@ +##' @importFrom FELLA generateResultsGraph +##' @importFrom tidygraph activate +##' @importFrom ggthemes ptol_pal +##' @importFrom dplyr mutate +##' @importFrom stringr str_split_fixed coll +##' @importFrom ggraph create_layout ggraph geom_edge_link geom_node_point geom_node_text theme_graph +##' @importFrom tibble tibble +##' @importFrom ggplot2 aes scale_colour_manual coord_fixed labs + +# setGeneric('plotGraph',function(x,comparison,type = 'diffusion'){ +# standardGeneric('plotGraph') +# }) +# +# setMethod('plotGraph',signature = 'FunctionalEnrichment', +# function(x,comparison,type = 'diffusion'){ +# en <- x@results[[comparison]] +# +# FELLA <- x@network +# +# pg <- generateResultsGraph(method = type,object = en,data = FELLA,nlimit = 1000,LabelLengthAtPlot = 100) %>% +# as_tbl_graph() %>% +# activate(nodes) +# +# types <- pg %>% +# nodes() %>% +# .$com +# +# types[types == 1] <- 'Pathway' +# types[types == 2] <- 'Module' +# types[types == 3] <- 'Enzyme' +# types[types == 4] <- 'Reaction' +# types[types == 5] <- 'Compound' +# +# pg <- pg %>% +# mutate(Type = factor(types,levels = c('Compound','Reaction','Enzyme','Module','Pathway')), +# label = str_split_fixed(label,coll(' - '),2)[,1]) +# +# pageLayout <- pg %>% +# create_layout('nicely') +# +# pagePathways <- pageLayout %>% +# filter(Type == 'Pathway') +# +# pageCompounds <- pageLayout %>% +# filter(Type == 'Compound') +# +# nudgey <- ({pageLayout$y %>% max()} - {pageLayout$y %>% min()}) / 25 +# +# colours <- tibble(Type = c('Compound','Reaction','Enzyme','Module','Pathway'), +# Colour = ptol_pal()(5)) +# +# ggraph(pageLayout) + +# geom_edge_link(alpha = 0.4) + +# geom_node_point(aes(colour = Type),size = 3,alpha = 0.5) + +# geom_node_text(data = pagePathways,aes(label = label),nudge_y = nudgey,size = 3,colour = 'black') + +# geom_node_text(data = pageCompounds,aes(label = label),nudge_y = nudgey,size = 3,colour = 'black') + +# scale_colour_manual(values = colours %>% filter(Type %in% unique(pg %>% nodes() %>% .$Type)) %>% .$Colour) + +# theme_graph(base_size = 11,base_family = '') + +# coord_fixed() + +# labs(title = comparison) +# } +# ) \ No newline at end of file diff --git a/R/plotGraph.R b/R/plotGraph.R deleted file mode 100644 index 2d4babd..0000000 --- a/R/plotGraph.R +++ /dev/null @@ -1,58 +0,0 @@ -#' @importFrom FELLA generateResultsGraph -#' @importFrom tidygraph activate -#' @importFrom ggthemes ptol_pal -#' @importFrom dplyr mutate -#' @importFrom stringr str_split_fixed coll -#' @importFrom ggraph create_layout ggraph geom_edge_link geom_node_point geom_node_text theme_graph -#' @importFrom tibble tibble -#' @importFrom ggplot2 aes scale_colour_manual coord_fixed labs - -setMethod('plotGraph',signature = 'FunctionalEnrichment', - function(x,comparison,type = 'diffusion'){ - en <- x@results[[comparison]] - - FELLA <- x@network - - pg <- generateResultsGraph(method = type,object = en,data = FELLA,nlimit = 1000,LabelLengthAtPlot = 100) %>% - as_tbl_graph() %>% - activate(nodes) - - types <- pg %>% - nodes() %>% - .$com - - types[types == 1] <- 'Pathway' - types[types == 2] <- 'Module' - types[types == 3] <- 'Enzyme' - types[types == 4] <- 'Reaction' - types[types == 5] <- 'Compound' - - pg <- pg %>% - mutate(Type = factor(types,levels = c('Compound','Reaction','Enzyme','Module','Pathway')), - label = str_split_fixed(label,coll(' - '),2)[,1]) - - pageLayout <- pg %>% - create_layout('nicely') - - pagePathways <- pageLayout %>% - filter(Type == 'Pathway') - - pageCompounds <- pageLayout %>% - filter(Type == 'Compound') - - nudgey <- ({pageLayout$y %>% max()} - {pageLayout$y %>% min()}) / 25 - - colours <- tibble(Type = c('Compound','Reaction','Enzyme','Module','Pathway'), - Colour = ptol_pal()(5)) - - ggraph(pageLayout) + - geom_edge_link(alpha = 0.4) + - geom_node_point(aes(colour = Type),size = 3,alpha = 0.5) + - geom_node_text(data = pagePathways,aes(label = label),nudge_y = nudgey,size = 3,colour = 'black') + - geom_node_text(data = pageCompounds,aes(label = label),nudge_y = nudgey,size = 3,colour = 'black') + - scale_colour_manual(values = colours %>% filter(Type %in% unique(pg %>% nodes() %>% .$Type)) %>% .$Colour) + - theme_graph(base_size = 11,base_family = '') + - coord_fixed() + - labs(title = comparison) - } -) \ No newline at end of file diff --git a/R/reexports.R b/R/reexports.R new file mode 100644 index 0000000..00b1b48 --- /dev/null +++ b/R/reexports.R @@ -0,0 +1,4 @@ +#' @importFrom magrittr %>% +#' @rdname reexports +#' @export +magrittr::`%>%` diff --git a/R/riches.R b/R/riches.R index 6dd369e..ca979af 100644 --- a/R/riches.R +++ b/R/riches.R @@ -1,2 +1,5 @@ -globalVariables(c('.','ACCESSION_ID','Name','Adduct','MF','Method','Pvalue','com','FELLA','label','Type','Response')) \ No newline at end of file +globalVariables(c('.','feature','n_comparisons','intensity','name','Name','MF','comparison','log2_ratio', + 'response','trend','nodes','com','NAME','level','classification','adjusted.p.value', + 'kingdom','level','metric','value','n','Not explanatory & in class','Explanatory & in class', + 'Explanatory & not in class','p.value')) \ No newline at end of file diff --git a/R/structural-classifications.R b/R/structural-classifications.R new file mode 100644 index 0000000..1f90369 --- /dev/null +++ b/R/structural-classifications.R @@ -0,0 +1,10 @@ +#' Example structural classifications +#' @format A tibble containing consensus structural classifications for the *m/z* features found +#' in the `assigned_data` example data set. +#' @source These example consensus structural classifications were generated using the +#' [{construction}](https://jasenfinch.github.io/construction/) package (v0.3.0) and are based on +#' the example analysis data (`assigned_data`) based on the *Brachypodium distachyon* ecotype +#' comparison FIE-MS metabolomic fingerprinting data set available in the +#' [{metaboData}](https://aberhrml.github.io/metaboData/) package. + +"structural_classifications" \ No newline at end of file diff --git a/R/structural-enrichment.R b/R/structural-enrichment.R new file mode 100644 index 0000000..299a01f --- /dev/null +++ b/R/structural-enrichment.R @@ -0,0 +1,398 @@ + +#' @importFrom broom tidy +#' @importFrom stats fisher.test + +overrepresentation <- function(explanatory_in_class, + not_explanatory_in_class, + explanatory_not_class, + not_explanatory_not_class){ + contingency <- matrix( + c(explanatory_in_class, + not_explanatory_in_class, + explanatory_not_class, + not_explanatory_not_class), + nrow = 2, + ncol = 2) + + fisher.test( + contingency, + alternative = 'greater' + ) %>% + tidy() +} + +featureInfo <- function(x){ + feature_info <- tibble( + Name = features(x) + ) %>% + separate( + Name, + c('Feature', + 'MF', + 'Isotope', + 'Adduct'), + sep = ' ', + fill = 'right', + remove = FALSE + ) + + feature_info[feature_info == ''] <- NA + + return(feature_info) +} + +setClass('StructuralEnrichment', + slots = list( + explanatory = 'tbl_df', + classifications = 'tbl_df', + results = 'tbl_df' + ), + contains = c('RandomForest')) + +setMethod('show',signature = 'StructuralEnrichment', + function(object){ + show(as(object,'RandomForest')) + + cat(length(unique(explanatoryFeatures(object)$feature)),'explanatory m/z features.\n') + structuralClassifications(object) %>% + select(-feature) %>% + gather(level,classification) %>% + drop_na() %>% + distinct() %>% + nrow() %>% + {cat(.,'structural classes total.\n')} + enrichmentResults(object) %>% + filter(adjusted.p.value < 0.05) %>% + nrow() %>% + cat(.,'significantly enriched structural classes.') + }) + +#' StructuralEnrichment S4 class accessors +#' @rdname structural-accessors +#' @description Accessor methods for the `StructuralEnrichment` S4 class. +#' @param x object of S4 class `StructuralEnrichment` +#' @return A tibble containing the accessed information. +#' @examples +#' ## Perform random forest on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class' +#' ) +#' +#' ## Perform functional enrichment analysis +#' enrichment_results <- structuralEnrichment( +#' random_forest, +#' structural_classifications +#' ) +#' +#' ## The m/z feature structural classifcations +#' structuralClassifications(enrichment_results) +#' +#' ## Access the explanatory features used for structural enrichment analysis +#' explanatoryFeatures(enrichment_results) +#' +#' ## Access the structral enrichment analysis results +#' enrichmentResults(enrichment_results) +#' @export + +setGeneric('structuralClassifications',function(x) + standardGeneric('structuralClassifications')) + +#' @rdname structural-accessors + +setMethod('structuralClassifications',signature = 'StructuralEnrichment', + function(x){ + x@classifications + }) + +#' @rdname structural-accessors +#' @export + +setMethod('explanatoryFeatures',signature = 'StructuralEnrichment', + function(x){ + x@explanatory + }) + +#' @rdname structural-accessors + +setMethod('enrichmentResults',signature = 'StructuralEnrichment', + function(x){ + x@results + }) + +#' Structural enrichment +#' @rdname structuralEnrichment +#' @description Perform structural enrichment using over-representation analysis of explanatory *m/z* features from random forest. +#' @param x an object of S4 class `RandomForest` +#' @param structural_classifications the structral classifications corresponding to the *m/z* features present in the object specified for argument `x`. This should either be a tibble as returned by `construction::classifications()` or an object of S4 class `Construction`. +#' @param p_adjust_method the p-value adjustment method. One of those returned from `p.adjust.methods`. +#' @param split split the explanatory features into further groups based on their trends. See details. +#' @param ... arguments to pass to `metabolyseR::explanatoryFeatures()` +#' @details +#' Over-representation analysis is performed on the explanatory *m/z* features for each structural class +#' within each experimental class comparison using the Fisher's Exact Test. +#' +#' For argument `split = 'trends'`, the explanatory features can be split into further groups +#' based on their trends. This is not supported for unsupervised random forest. +#' +#' For random forest classification, this is for binary comparisons only. Functional enrichment +#' is performed seperately on the up and down regulated explanatory features for each comparison. The +#' `up regulated` and `down regulated` groups are based on the trends of log2 ratios between +#' the comparison classes. `up regulated` explanatory features have a higher median intensity +#' in the right-hand class compared to the left-hand class of the comparison. The opposite is true +#' for the `down regulated` explanatory features. +#' +#' For random forest regression, the explanatory features are split based on their Spearman's +#' correlation coefficient with the response variable prior to functional enrichment analysis +#' giving `positively correlated` and `negatively correlated` subgroups. +#' @return An object of S4 class `StructuralEnrichment`. +#' @examples +#' ## Perform random forest on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class' +#' ) +#' +#' ## Perform structural enrichment analysis using the example structural classifications +#' structuralEnrichment( +#' random_forest, +#' structural_classifications +#' ) +#' +#' ## An example using split trends +#' ## Perform random forest on the example data +#' random_forest <- assigned_data %>% +#' metabolyseR::randomForest( +#' cls = 'class', +#' binary = TRUE +#' ) +#' +#' ## Perform structural enrichment analysis using the example structural classifications +#' structuralEnrichment( +#' random_forest, +#' structural_classifications, +#' split = 'trends' +#' ) +#' @export + +setGeneric('structuralEnrichment',function(x, + structural_classifications, + p_adjust_method = 'bonferroni', + split = c('none','trends'), + ...) + standardGeneric('structuralEnrichment')) + +#' @rdname structuralEnrichment +#' @importFrom dplyr inner_join group_by count group_map rowwise bind_cols relocate arrange mutate any_of +#' @importFrom tidyr gather drop_na +#' @importFrom tidyselect last_col +#' @importFrom metabolyseR nFeatures +#' @importFrom stats p.adjust + +setMethod('structuralEnrichment',signature = c('RandomForest','tbl_df'), + function(x, + structural_classifications, + p_adjust_method = 'bonferroni', + split = c('none','trends'), + ...){ + + rf_type <- type(x) + + split <- match.arg(split, + choices = c( + 'none', + 'trends' + )) + + explanatory_features <- explanatoryFeatures(x,...) + + if (split == 'trends'){ + explanatory_features <- trends(x,explanatory_features) + } + + feature_classifications <- structural_classifications %>% + select(-Name) %>% + inner_join(featureInfo(x), + by = c('Feature', 'MF', 'Isotope', 'Adduct')) %>% + select(feature = Name,kingdom:last_col(offset = 2)) + + background_classification_totals <- feature_classifications %>% + gather(level,classification,-feature) %>% + drop_na() %>% + group_by(level,classification) %>% + count() + + explanatory_classifications <- explanatory_features %>% + select(-metric,-value, + -any_of(c('p-value','adjusted_p-value','ratio','log2_ratio','correlation'))) %>% + left_join(feature_classifications, + by = 'feature') + + if (rf_type == 'classification'){ + explanatory_classifications <- explanatory_classifications %>% + group_by(response,comparison) + } + + if (rf_type == 'regression'){ + explanatory_classifications <- explanatory_classifications %>% + group_by(response) + } + + if (split == 'trends'){ + explanatory_classifications <- explanatory_classifications %>% + group_by(trend,.add = TRUE) + } + + explanatory_totals <- explanatory_classifications %>% + count() + + if (rf_type == 'classification'){ + explanatory_classification_totals <- explanatory_classifications %>% + gather(level,classification, + -any_of(c( + 'response', + 'comparison', + 'feature', + 'trend')) + )%>% + drop_na() %>% + group_by(response,comparison,level,classification) + + if (split == 'trends'){ + explanatory_classification_totals <- explanatory_classification_totals %>% + group_by(trend,.add = TRUE) + } + explanatory_classification_totals <- explanatory_classification_totals %>% + count() + } + + if (rf_type == 'regression'){ + explanatory_classification_totals <- explanatory_classifications %>% + gather(level,classification, + -any_of(c('response', + 'feature', + 'trend'))) %>% + drop_na() %>% + group_by(response,level,classification) + + if (split == 'trends'){ + explanatory_classification_totals <- explanatory_classification_totals %>% + group_by(trend,.add = TRUE) + } + explanatory_classification_totals <- explanatory_classification_totals %>% + count() + } + + if (rf_type == 'unsupervised'){ + explanatory_classification_totals <- explanatory_classifications %>% + gather(level,classification,-feature) %>% + drop_na() %>% + group_by(level,classification) %>% + count() + } + + contingency <- explanatory_classification_totals %>% + rename(`Explanatory & in class` = n) %>% + left_join(background_classification_totals, + by = c('level','classification')) %>% + rename(`Not explanatory & in class` = n) %>% + mutate(`Not explanatory & in class` = `Not explanatory & in class` - + `Explanatory & in class`) + + if (rf_type == 'classification'){ + by <- c('response','comparison') + + if (split == 'trends'){ + by <- c(by,'trend') + } + + contingency <- contingency %>% + left_join(explanatory_totals,by = by) + } + + if (rf_type == 'regression'){ + by <- 'response' + + if (split == 'trends'){ + by <- c(by,'trend') + } + + contingency <- contingency %>% + left_join(explanatory_totals,by = by) + } + + if (rf_type == 'unsupervised'){ + contingency <- contingency %>% + mutate(n = explanatory_totals$n[1]) + } + + contingency <- contingency %>% + rename(`Explanatory & not in class` = n) %>% + mutate(`Explanatory & not in class` = `Explanatory & not in class` - + `Explanatory & in class`, + `Not explanatory & not in class` = nFeatures(x) - + (`Explanatory & in class` + `Not explanatory & in class`) - + `Explanatory & not in class`) + + ora_results <- contingency %>% + rowwise() %>% + group_map( + ~bind_cols(.x, + overrepresentation( + .x$`Explanatory & in class`, + .x$`Not explanatory & in class`, + .x$`Explanatory & not in class`, + .x$`Not explanatory & not in class`) + ) + ) %>% + bind_rows() + + if (rf_type == 'classification'){ + ora_results <- ora_results %>% + group_by(response,comparison) + } + + if (rf_type == 'regression'){ + ora_results <- ora_results %>% + group_by(response) + } + + if (split == 'trends'){ + ora_results <- ora_results %>% + group_by(trend,.add = TRUE) + } + + ora_results <- ora_results %>% + mutate( + adjusted.p.value = p.adjust(p.value,method = p_adjust_method) + ) %>% + relocate(adjusted.p.value,.after = p.value) %>% + ungroup() %>% + arrange(p.value) + + results <- new('StructuralEnrichment', + x, + explanatory = explanatory_features, + classifications = feature_classifications, + results = ora_results) + + return(results) + }) + +#' @rdname structuralEnrichment +#' @importFrom construction classifications +#' @importFrom dplyr ungroup + +setMethod('structuralEnrichment',signature = c('RandomForest','Construction'), + function(x, + structural_classifications, + p_adjust_method = 'bonferroni', + split = c('none','trends'), + ...){ + structural_classifications <- classifications(structural_classifications) + + structuralEnrichment(x = x, + structural_classifications = structural_classifications, + p_adjust_method = p_adjust_method, + split = split) + }) \ No newline at end of file diff --git a/R/sysdata.rda b/R/sysdata.rda index 29b283d..871fd17 100644 Binary files a/R/sysdata.rda and b/R/sysdata.rda differ diff --git a/R/trends.R b/R/trends.R new file mode 100644 index 0000000..45b32cc --- /dev/null +++ b/R/trends.R @@ -0,0 +1,143 @@ + +trendType <- function(x){ + rf_type <- type(x) + + switch( + rf_type, + unsupervised = stop('Trends cannot be used for unsuperised random forest.',call. = FALSE), + classification = 'ratio', + regression = 'correlation' + ) +} + +#' @importFrom stringr str_extract_all + +checkComparisons <- function(explanatory_features){ + comparisons <- explanatory_features %>% + select(comparison,feature) %>% + mutate(n_comparisons = comparison %>% + str_extract_all('~') %>% + nchar()) + + if (any(comparisons$n_comparisons > 1)){ + non_binary <- comparisons %>% + select(comparison,n_comparisons) %>% + distinct() %>% + filter(n_comparisons > 1) %>% + .$comparison + + warning(paste0( + 'Trends only possible for binary comparisons. Comparisons ', + paste(non_binary,collapse = ', '), + ' will be removed.'), + call. = FALSE + ) + + explanatory_features <- explanatory_features %>% + filter(!comparison %in% non_binary) + } + + if (nrow(explanatory_features) == 0){ + stop('No binary comparisons available to calculate trends.', + call. = FALSE) + } + + return(explanatory_features) +} + +#' @importFrom metabolyseR sinfo keepFeatures dat +#' @importFrom rlang sym +#' @importFrom tidyr spread +#' @importFrom dplyr summarise all_of +#' @importFrom stats median + +ratio <- function(x,explanatory_features){ + + explanatory_features <- checkComparisons(explanatory_features) + + comparisons <- explanatory_features %>% + select(comparison,feature) %>% + separate( + comparison, + c('class1','class2'), + sep = '~', + remove = FALSE + ) + + explanatory_feature_data <- x %>% + keepFeatures( + features = unique(explanatory_features$feature) + ) %>% + { + d <- . + + dat(d) %>% + bind_cols( + sinfo(d) %>% + select(all_of(explanatory_features$response[1])) + ) + } %>% + gather(feature,intensity,-!!explanatory_features$response[1]) %>% + group_by(!!sym(explanatory_features$response[1]),feature) %>% + summarise(median = median(intensity), + .groups = 'drop') %>% + spread(!!explanatory_features$response[1],median) + + ratios <- comparisons %>% + left_join(explanatory_feature_data, + by = 'feature') %>% + mutate(ratio = !!sym(.$class2[1]) / !!sym(.$class1[1]), + log2_ratio = log2(ratio)) %>% + select(comparison,feature,ratio,log2_ratio) %>% + mutate( + trend = ifelse(log2_ratio < 0,'down regulated','up regulated') + ) + + explanatory_features <- explanatory_features %>% + left_join(ratios, + by = c('comparison', + 'feature')) + + return(explanatory_features) + +} + +#' @importFrom stats cor + +correlation <- function(x,explanatory_features){ + correlations <- x %>% + keepFeatures( + features = unique(explanatory_features$feature) + ) %>% + { + d <- . + + dat(d) %>% + bind_cols( + sinfo(d) %>% + select(all_of(explanatory_features$response[1])) + ) + } %>% + gather(feature,intensity,-!!explanatory_features$response[1]) %>% + group_by(feature) %>% + summarise(correlation = cor(!!sym(explanatory_features$response[1]), + intensity, + method = 'spearman'), + .groups = 'drop') %>% + mutate( + trend = ifelse(correlation < 0,'negatively correlated','positively correlated') + ) + + explanatory_features %>% + left_join(correlations, + by = 'feature') +} + +trends <- function(x,explanatory_features){ + trend_type <- trendType(x) + + explanatory_features <- do.call(trend_type, + list(x = x,explanatory_features = explanatory_features)) + + return(explanatory_features) +} \ No newline at end of file diff --git a/README.md b/README.md index d888a92..0d457e1 100644 --- a/README.md +++ b/README.md @@ -3,11 +3,12 @@ [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental) -[![R build status](https://github.com/jasenfinch/riches/workflows/R-CMD-check/badge.svg)](https://github.com/jasenfinch/riches/actions) +[![R-CMD-check](https://github.com/jasenfinch/riches/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/jasenfinch/riches/actions/workflows/R-CMD-check.yaml) [![Codecov test coverage](https://codecov.io/gh/jasenfinch/riches/branch/master/graph/badge.svg)](https://codecov.io/gh/jasenfinch/riches?branch=master) +[![GitHub release](https://img.shields.io/github/release/jasenfinch/riches.svg)](https://GitHub.com/jasenfinch/riches/releases/) -Structural and functional enrichment for metabolomics data. +> Structural and functional enrichment for metabolomics data. ## Installation @@ -17,5 +18,13 @@ The `riches` package can be installed from GitHub using: remotes::install_github('jasenfinch/riches') ``` +## Learn more + +The package documentation can be browsed online at . + +If you believe you've found a bug in `riches`, please file a bug (and, if +possible, a [reproducible example](https://reprex.tidyverse.org)) at +. + diff --git a/_pkgdown.yml b/_pkgdown.yml new file mode 100644 index 0000000..2020e67 --- /dev/null +++ b/_pkgdown.yml @@ -0,0 +1,4 @@ +url: https://jasenfinch.github.io/riches/ +template: + bootstrap: 5 + diff --git a/data/assigned_data.RData b/data/assigned_data.RData new file mode 100644 index 0000000..f1f337b Binary files /dev/null and b/data/assigned_data.RData differ diff --git a/data/example_analysis.RData b/data/example_analysis.RData deleted file mode 100644 index c96349d..0000000 Binary files a/data/example_analysis.RData and /dev/null differ diff --git a/data/example_assignment.RData b/data/example_assignment.RData deleted file mode 100644 index 8676f0f..0000000 Binary files a/data/example_assignment.RData and /dev/null differ diff --git a/data/structural_classifications.RData b/data/structural_classifications.RData new file mode 100644 index 0000000..f76d3b9 Binary files /dev/null and b/data/structural_classifications.RData differ diff --git a/docs/404.html b/docs/404.html deleted file mode 100644 index 701b5fc..0000000 --- a/docs/404.html +++ /dev/null @@ -1,145 +0,0 @@ - - - - - - - - -Page not found (404) • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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“Additional permissions” are terms that supplement the terms of this License by making exceptions from one or more of its conditions. Additional permissions that are applicable to the entire Program shall be treated as though they were included in this License, to the extent that they are valid under applicable law. If additional permissions apply only to part of the Program, that part may be used separately under those permissions, but the entire Program remains governed by this License without regard to the additional permissions.

-

When you convey a copy of a covered work, you may at your option remove any additional permissions from that copy, or from any part of it. (Additional permissions may be written to require their own removal in certain cases when you modify the work.) You may place additional permissions on material, added by you to a covered work, for which you have or can give appropriate copyright permission.

-

Notwithstanding any other provision of this License, for material you add to a covered work, you may (if authorized by the copyright holders of that material) supplement the terms of this License with terms:

-
    -
  • -a) Disclaiming warranty or limiting liability differently from the terms of sections 15 and 16 of this License; or
  • -
  • -b) Requiring preservation of specified reasonable legal notices or author attributions in that material or in the Appropriate Legal Notices displayed by works containing it; or
  • -
  • -c) Prohibiting misrepresentation of the origin of that material, or requiring that modified versions of such material be marked in reasonable ways as different from the original version; or
  • -
  • -d) Limiting the use for publicity purposes of names of licensors or authors of the material; or
  • -
  • -e) Declining to grant rights under trademark law for use of some trade names, trademarks, or service marks; or
  • -
  • -f) Requiring indemnification of licensors and authors of that material by anyone who conveys the material (or modified versions of it) with contractual assumptions of liability to the recipient, for any liability that these contractual assumptions directly impose on those licensors and authors.
  • -
-

All other non-permissive additional terms are considered “further restrictions” within the meaning of section 10. If the Program as you received it, or any part of it, contains a notice stating that it is governed by this License along with a term that is a further restriction, you may remove that term. If a license document contains a further restriction but permits relicensing or conveying under this License, you may add to a covered work material governed by the terms of that license document, provided that the further restriction does not survive such relicensing or conveying.

-

If you add terms to a covered work in accord with this section, you must place, in the relevant source files, a statement of the additional terms that apply to those files, or a notice indicating where to find the applicable terms.

-

Additional terms, permissive or non-permissive, may be stated in the form of a separately written license, or stated as exceptions; the above requirements apply either way.

-
-
-

-8. Termination

-

You may not propagate or modify a covered work except as expressly provided under this License. Any attempt otherwise to propagate or modify it is void, and will automatically terminate your rights under this License (including any patent licenses granted under the third paragraph of section 11).

-

However, if you cease all violation of this License, then your license from a particular copyright holder is reinstated (a) provisionally, unless and until the copyright holder explicitly and finally terminates your license, and (b) permanently, if the copyright holder fails to notify you of the violation by some reasonable means prior to 60 days after the cessation.

-

Moreover, your license from a particular copyright holder is reinstated permanently if the copyright holder notifies you of the violation by some reasonable means, this is the first time you have received notice of violation of this License (for any work) from that copyright holder, and you cure the violation prior to 30 days after your receipt of the notice.

-

Termination of your rights under this section does not terminate the licenses of parties who have received copies or rights from you under this License. If your rights have been terminated and not permanently reinstated, you do not qualify to receive new licenses for the same material under section 10.

-
-
-

-9. Acceptance Not Required for Having Copies

-

You are not required to accept this License in order to receive or run a copy of the Program. Ancillary propagation of a covered work occurring solely as a consequence of using peer-to-peer transmission to receive a copy likewise does not require acceptance. However, nothing other than this License grants you permission to propagate or modify any covered work. These actions infringe copyright if you do not accept this License. Therefore, by modifying or propagating a covered work, you indicate your acceptance of this License to do so.

-
-
-

-10. Automatic Licensing of Downstream Recipients

-

Each time you convey a covered work, the recipient automatically receives a license from the original licensors, to run, modify and propagate that work, subject to this License. You are not responsible for enforcing compliance by third parties with this License.

-

An “entity transaction” is a transaction transferring control of an organization, or substantially all assets of one, or subdividing an organization, or merging organizations. If propagation of a covered work results from an entity transaction, each party to that transaction who receives a copy of the work also receives whatever licenses to the work the party’s predecessor in interest had or could give under the previous paragraph, plus a right to possession of the Corresponding Source of the work from the predecessor in interest, if the predecessor has it or can get it with reasonable efforts.

-

You may not impose any further restrictions on the exercise of the rights granted or affirmed under this License. For example, you may not impose a license fee, royalty, or other charge for exercise of rights granted under this License, and you may not initiate litigation (including a cross-claim or counterclaim in a lawsuit) alleging that any patent claim is infringed by making, using, selling, offering for sale, or importing the Program or any portion of it.

-
-
-

-11. Patents

-

A “contributor” is a copyright holder who authorizes use under this License of the Program or a work on which the Program is based. The work thus licensed is called the contributor’s “contributor version”.

-

A contributor’s “essential patent claims” are all patent claims owned or controlled by the contributor, whether already acquired or hereafter acquired, that would be infringed by some manner, permitted by this License, of making, using, or selling its contributor version, but do not include claims that would be infringed only as a consequence of further modification of the contributor version. For purposes of this definition, “control” includes the right to grant patent sublicenses in a manner consistent with the requirements of this License.

-

Each contributor grants you a non-exclusive, worldwide, royalty-free patent license under the contributor’s essential patent claims, to make, use, sell, offer for sale, import and otherwise run, modify and propagate the contents of its contributor version.

-

In the following three paragraphs, a “patent license” is any express agreement or commitment, however denominated, not to enforce a patent (such as an express permission to practice a patent or covenant not to sue for patent infringement). To “grant” such a patent license to a party means to make such an agreement or commitment not to enforce a patent against the party.

-

If you convey a covered work, knowingly relying on a patent license, and the Corresponding Source of the work is not available for anyone to copy, free of charge and under the terms of this License, through a publicly available network server or other readily accessible means, then you must either (1) cause the Corresponding Source to be so available, or (2) arrange to deprive yourself of the benefit of the patent license for this particular work, or (3) arrange, in a manner consistent with the requirements of this License, to extend the patent license to downstream recipients. “Knowingly relying” means you have actual knowledge that, but for the patent license, your conveying the covered work in a country, or your recipient’s use of the covered work in a country, would infringe one or more identifiable patents in that country that you have reason to believe are valid.

-

If, pursuant to or in connection with a single transaction or arrangement, you convey, or propagate by procuring conveyance of, a covered work, and grant a patent license to some of the parties receiving the covered work authorizing them to use, propagate, modify or convey a specific copy of the covered work, then the patent license you grant is automatically extended to all recipients of the covered work and works based on it.

-

A patent license is “discriminatory” if it does not include within the scope of its coverage, prohibits the exercise of, or is conditioned on the non-exercise of one or more of the rights that are specifically granted under this License. You may not convey a covered work if you are a party to an arrangement with a third party that is in the business of distributing software, under which you make payment to the third party based on the extent of your activity of conveying the work, and under which the third party grants, to any of the parties who would receive the covered work from you, a discriminatory patent license (a) in connection with copies of the covered work conveyed by you (or copies made from those copies), or (b) primarily for and in connection with specific products or compilations that contain the covered work, unless you entered into that arrangement, or that patent license was granted, prior to 28 March 2007.

-

Nothing in this License shall be construed as excluding or limiting any implied license or other defenses to infringement that may otherwise be available to you under applicable patent law.

-
-
-

-12. No Surrender of Others’ Freedom

-

If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may not convey it at all. For example, if you agree to terms that obligate you to collect a royalty for further conveying from those to whom you convey the Program, the only way you could satisfy both those terms and this License would be to refrain entirely from conveying the Program.

-
-
-

-13. Use with the GNU Affero General Public License

-

Notwithstanding any other provision of this License, you have permission to link or combine any covered work with a work licensed under version 3 of the GNU Affero General Public License into a single combined work, and to convey the resulting work. The terms of this License will continue to apply to the part which is the covered work, but the special requirements of the GNU Affero General Public License, section 13, concerning interaction through a network will apply to the combination as such.

-
-
-

-14. Revised Versions of this License

-

The Free Software Foundation may publish revised and/or new versions of the GNU General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns.

-

Each version is given a distinguishing version number. If the Program specifies that a certain numbered version of the GNU General Public License “or any later version” applies to it, you have the option of following the terms and conditions either of that numbered version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of the GNU General Public License, you may choose any version ever published by the Free Software Foundation.

-

If the Program specifies that a proxy can decide which future versions of the GNU General Public License can be used, that proxy’s public statement of acceptance of a version permanently authorizes you to choose that version for the Program.

-

Later license versions may give you additional or different permissions. However, no additional obligations are imposed on any author or copyright holder as a result of your choosing to follow a later version.

-
-
-

-15. Disclaimer of Warranty

-

THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.

-
-
-

-16. Limitation of Liability

-

IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

-
-
-

-17. Interpretation of Sections 15 and 16

-

If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.

-

END OF TERMS AND CONDITIONS

-
-
-
-

-How to Apply These Terms to Your New Programs

-

If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.

-

To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the “copyright” line and a pointer to where the full notice is found.

-
<one line to give the program's name and a brief idea of what it does.>
-Copyright (C) 2020 Jasen Finch
-
-This program is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-This program is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with this program.  If not, see <http://www.gnu.org/licenses/>.
-

Also add information on how to contact you by electronic and paper mail.

-

If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:

-
riches Copyright (C) 2020 Jasen Finch
-This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'.
-This is free software, and you are welcome to redistribute it
-under certain conditions; type 'show c' for details.
-

The hypothetical commands show w and show c should show the appropriate parts of the General Public License. Of course, your program’s commands might be different; for a GUI interface, you would use an “about box”.

-

You should also get your employer (if you work as a programmer) or school, if any, to sign a “copyright disclaimer” for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see <http://www.gnu.org/licenses/>.

-

The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read <http://www.gnu.org/philosophy/why-not-lgpl.html>.

-
-
- -
- - - -
- - - -
- - -
-

Site built with pkgdown 1.6.1.

-
- -
-
- - - - - - - - diff --git a/docs/authors.html b/docs/authors.html deleted file mode 100644 index 2dd15a4..0000000 --- a/docs/authors.html +++ /dev/null @@ -1,144 +0,0 @@ - - - - - - - - -Authors • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-
- - - - -
- -
-
- - -
    -
  • -

    Jasen Finch. Author, maintainer. -

    -
  • -
- -
- -
- - - -
- - -
-

Site built with pkgdown 1.6.1.

-
- -
-
- - - - - - - - diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css deleted file mode 100644 index 5a85941..0000000 --- a/docs/bootstrap-toc.css +++ /dev/null @@ -1,60 +0,0 @@ -/*! - * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) - * Copyright 2015 Aidan Feldman - * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ - -/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */ - -/* All levels of nav */ -nav[data-toggle='toc'] .nav > li > a { - display: block; - padding: 4px 20px; - font-size: 13px; - font-weight: 500; - color: #767676; -} -nav[data-toggle='toc'] .nav > li > a:hover, -nav[data-toggle='toc'] .nav > li > a:focus { - padding-left: 19px; - color: #563d7c; - text-decoration: none; - background-color: transparent; - border-left: 1px solid #563d7c; -} -nav[data-toggle='toc'] .nav > .active > a, -nav[data-toggle='toc'] .nav > .active:hover > a, -nav[data-toggle='toc'] .nav > .active:focus > a { - padding-left: 18px; - font-weight: bold; - color: #563d7c; - background-color: transparent; - border-left: 2px solid #563d7c; -} - -/* Nav: second level (shown on .active) */ -nav[data-toggle='toc'] .nav .nav { - display: none; /* Hide by default, but at >768px, show it */ - padding-bottom: 10px; -} -nav[data-toggle='toc'] .nav .nav > li > a { - padding-top: 1px; - padding-bottom: 1px; - padding-left: 30px; - font-size: 12px; - font-weight: normal; -} -nav[data-toggle='toc'] .nav .nav > li > a:hover, -nav[data-toggle='toc'] .nav .nav > li > a:focus { - padding-left: 29px; -} -nav[data-toggle='toc'] .nav .nav > .active > a, -nav[data-toggle='toc'] .nav .nav > .active:hover > a, -nav[data-toggle='toc'] .nav .nav > .active:focus > a { - padding-left: 28px; - font-weight: 500; -} - -/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */ -nav[data-toggle='toc'] .nav > .active > ul { - display: block; -} diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js deleted file mode 100644 index 1cdd573..0000000 --- a/docs/bootstrap-toc.js +++ /dev/null @@ -1,159 +0,0 @@ -/*! - * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) - * Copyright 2015 Aidan Feldman - * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ -(function() { - 'use strict'; - - window.Toc = { - helpers: { - // return all matching elements in the set, or their descendants - findOrFilter: function($el, selector) { - // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/ - // http://stackoverflow.com/a/12731439/358804 - var $descendants = $el.find(selector); - return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])'); - }, - - generateUniqueIdBase: function(el) { - var text = $(el).text(); - var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-'); - return anchor || el.tagName.toLowerCase(); - }, - - generateUniqueId: function(el) { - var anchorBase = this.generateUniqueIdBase(el); - for (var i = 0; ; i++) { - var anchor = anchorBase; - if (i > 0) { - // add suffix - anchor += '-' + i; - } - // check if ID already exists - if (!document.getElementById(anchor)) { - return anchor; - } - } - }, - - generateAnchor: function(el) { - if (el.id) { - return el.id; - } else { - var anchor = this.generateUniqueId(el); - el.id = anchor; - return anchor; - } - }, - - createNavList: function() { - return $(''); - }, - - createChildNavList: function($parent) { - var $childList = this.createNavList(); - $parent.append($childList); - return $childList; - }, - - generateNavEl: function(anchor, text) { - var $a = $(''); - $a.attr('href', '#' + anchor); - $a.text(text); - var $li = $('
  • '); - $li.append($a); - return $li; - }, - - generateNavItem: function(headingEl) { - var anchor = this.generateAnchor(headingEl); - var $heading = $(headingEl); - var text = $heading.data('toc-text') || $heading.text(); - return this.generateNavEl(anchor, text); - }, - - // Find the first heading level (`

    `, then `

    `, etc.) that has more than one element. Defaults to 1 (for `

    `). - getTopLevel: function($scope) { - for (var i = 1; i <= 6; i++) { - var $headings = this.findOrFilter($scope, 'h' + i); - if ($headings.length > 1) { - return i; - } - } - - return 1; - }, - - // returns the elements for the top level, and the next below it - getHeadings: function($scope, topLevel) { - var topSelector = 'h' + topLevel; - - var secondaryLevel = topLevel + 1; - var secondarySelector = 'h' + secondaryLevel; - - return this.findOrFilter($scope, topSelector + ',' + secondarySelector); - }, - - getNavLevel: function(el) { - return parseInt(el.tagName.charAt(1), 10); - }, - - populateNav: function($topContext, topLevel, $headings) { - var $context = $topContext; - var $prevNav; - - var helpers = this; - $headings.each(function(i, el) { - var $newNav = helpers.generateNavItem(el); - var navLevel = helpers.getNavLevel(el); - - // determine the proper $context - if (navLevel === topLevel) { - // use top level - $context = $topContext; - } else if ($prevNav && $context === $topContext) { - // create a new level of the tree and switch to it - $context = helpers.createChildNavList($prevNav); - } // else use the current $context - - $context.append($newNav); - - $prevNav = $newNav; - }); - }, - - parseOps: function(arg) { - var opts; - if (arg.jquery) { - opts = { - $nav: arg - }; - } else { - opts = arg; - } - opts.$scope = opts.$scope || $(document.body); - return opts; - } - }, - - // accepts a jQuery object, or an options object - init: function(opts) { - opts = this.helpers.parseOps(opts); - - // ensure that the data attribute is in place for styling - opts.$nav.attr('data-toggle', 'toc'); - - var $topContext = this.helpers.createChildNavList(opts.$nav); - var topLevel = this.helpers.getTopLevel(opts.$scope); - var $headings = this.helpers.getHeadings(opts.$scope, topLevel); - this.helpers.populateNav($topContext, topLevel, $headings); - } - }; - - $(function() { - $('nav[data-toggle="toc"]').each(function(i, el) { - var $nav = $(el); - Toc.init($nav); - }); - }); -})(); diff --git a/docs/docsearch.css b/docs/docsearch.css deleted file mode 100644 index e5f1fe1..0000000 --- a/docs/docsearch.css +++ /dev/null @@ -1,148 +0,0 @@ -/* Docsearch -------------------------------------------------------------- */ -/* - Source: https://github.com/algolia/docsearch/ - License: MIT -*/ - -.algolia-autocomplete { - display: block; - -webkit-box-flex: 1; - -ms-flex: 1; - flex: 1 -} - -.algolia-autocomplete .ds-dropdown-menu { - width: 100%; - min-width: none; - max-width: none; - padding: .75rem 0; - background-color: #fff; - background-clip: padding-box; - border: 1px solid rgba(0, 0, 0, .1); - box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175); -} - -@media (min-width:768px) { - .algolia-autocomplete .ds-dropdown-menu { - width: 175% - } -} - -.algolia-autocomplete .ds-dropdown-menu::before { - display: none -} - -.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] { - padding: 0; - background-color: rgb(255,255,255); - border: 0; - max-height: 80vh; -} - -.algolia-autocomplete .ds-dropdown-menu .ds-suggestions { - margin-top: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion { - padding: 0; - overflow: visible -} - -.algolia-autocomplete .algolia-docsearch-suggestion--category-header { - padding: .125rem 1rem; - margin-top: 0; - font-size: 1.3em; - font-weight: 500; - color: #00008B; - border-bottom: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--wrapper { - float: none; - padding-top: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column { - float: none; - width: auto; - padding: 0; - text-align: left -} - -.algolia-autocomplete .algolia-docsearch-suggestion--content { - float: none; - width: auto; - padding: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--content::before { - display: none -} - -.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header { - padding-top: .75rem; - margin-top: .75rem; - border-top: 1px solid rgba(0, 0, 0, .1) -} - -.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column { - display: block; - padding: .1rem 1rem; - margin-bottom: 0.1; - font-size: 1.0em; - font-weight: 400 - /* display: none */ -} - -.algolia-autocomplete .algolia-docsearch-suggestion--title { - display: block; - padding: .25rem 1rem; - margin-bottom: 0; - font-size: 0.9em; - font-weight: 400 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--text { - padding: 0 1rem .5rem; - margin-top: -.25rem; - font-size: 0.8em; - font-weight: 400; - line-height: 1.25 -} - -.algolia-autocomplete .algolia-docsearch-footer { - width: 110px; - height: 20px; - z-index: 3; - margin-top: 10.66667px; - float: right; - font-size: 0; - line-height: 0; -} - -.algolia-autocomplete .algolia-docsearch-footer--logo { - background-image: url("data:image/svg+xml;utf8,"); - background-repeat: no-repeat; - background-position: 50%; - background-size: 100%; - overflow: hidden; - text-indent: -9000px; - width: 100%; - height: 100%; - display: block; - transform: translate(-8px); -} - -.algolia-autocomplete .algolia-docsearch-suggestion--highlight { - color: #FF8C00; - background: rgba(232, 189, 54, 0.1) -} - - -.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight { - box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5) -} - -.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content { - background-color: rgba(192, 192, 192, .15) -} diff --git a/docs/docsearch.js b/docs/docsearch.js deleted file mode 100644 index b35504c..0000000 --- a/docs/docsearch.js +++ /dev/null @@ -1,85 +0,0 @@ -$(function() { - - // register a handler to move the focus to the search bar - // upon pressing shift + "/" (i.e. "?") - $(document).on('keydown', function(e) { - if (e.shiftKey && e.keyCode == 191) { - e.preventDefault(); - $("#search-input").focus(); - } - }); - - $(document).ready(function() { - // do keyword highlighting - /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */ - var mark = function() { - - var referrer = document.URL ; - var paramKey = "q" ; - - if (referrer.indexOf("?") !== -1) { - var qs = referrer.substr(referrer.indexOf('?') + 1); - var qs_noanchor = qs.split('#')[0]; - var qsa = qs_noanchor.split('&'); - var keyword = ""; - - for (var i = 0; i < qsa.length; i++) { - var currentParam = qsa[i].split('='); - - if (currentParam.length !== 2) { - continue; - } - - if (currentParam[0] == paramKey) { - keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20")); - } - } - - if (keyword !== "") { - $(".contents").unmark({ - done: function() { - $(".contents").mark(keyword); - } - }); - } - } - }; - - mark(); - }); -}); - -/* Search term highlighting ------------------------------*/ - -function matchedWords(hit) { - var words = []; - - var hierarchy = hit._highlightResult.hierarchy; - // loop to fetch from lvl0, lvl1, etc. - for (var idx in hierarchy) { - words = words.concat(hierarchy[idx].matchedWords); - } - - var content = hit._highlightResult.content; - if (content) { - words = words.concat(content.matchedWords); - } - - // return unique words - var words_uniq = [...new Set(words)]; - return words_uniq; -} - -function updateHitURL(hit) { - - var words = matchedWords(hit); - var url = ""; - - if (hit.anchor) { - url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor; - } else { - url = hit.url + '?q=' + escape(words.join(" ")); - } - - return url; -} diff --git a/docs/index.html b/docs/index.html deleted file mode 100644 index 20b19ad..0000000 --- a/docs/index.html +++ /dev/null @@ -1,136 +0,0 @@ - - - - - - - -Strucutral and Functional Enrichment Analyses • riches - - - - - - - - - - -
    -
    - - - - -
    -
    -
    - - - -

    Structural and functional enrichment for metabolomics data.

    -
    -

    -Installation

    -

    The riches package can be installed from GitHub using:

    -
    -remotes::install_github('jasenfinch/riches')
    -
    -
    -
    - - -
    - - -
    - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - diff --git a/docs/link.svg b/docs/link.svg deleted file mode 100644 index 88ad827..0000000 --- a/docs/link.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - diff --git a/docs/pkgdown.css b/docs/pkgdown.css deleted file mode 100644 index 1273238..0000000 --- a/docs/pkgdown.css +++ /dev/null @@ -1,367 +0,0 @@ -/* Sticky footer */ - -/** - * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/ - * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css - * - * .Site -> body > .container - * .Site-content -> body > .container .row - * .footer -> footer - * - * Key idea seems to be to ensure that .container and __all its parents__ - * have height set to 100% - * - */ - -html, body { - height: 100%; -} - -body { - position: relative; -} - -body > .container { - display: flex; - height: 100%; - flex-direction: column; -} - -body > .container .row { - flex: 1 0 auto; -} - -footer { - margin-top: 45px; - padding: 35px 0 36px; 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    -
    - - - - -
    - -
    -
    - - -
    -

    Retrieve or set enrichment parameters.

    -
    - -
    functional(x)
    -
    -functional(x) <- value
    -
    -# S4 method for EnrichmentParameters
    -functional(x)
    -
    -# S4 method for EnrichmentParameters
    -functional(x) <- value
    - -

    Arguments

    - - - - - - - - - - -
    x

    S4 object of class EnrichmentParameters

    value

    value to set

    - - -
    - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png deleted file mode 100644 index 17a3580..0000000 Binary files a/docs/reference/Rplot001.png and /dev/null differ diff --git a/docs/reference/enrichmentParameters.html b/docs/reference/enrichmentParameters.html deleted file mode 100644 index 2deb395..0000000 --- a/docs/reference/enrichmentParameters.html +++ /dev/null @@ -1,176 +0,0 @@ - - - - - - - - -enrichmentParameters — enrichmentParameters • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - -
    -

    Enrichment parameters.

    -
    - -
    enrichmentParameters(
    -  organism,
    -  model = "randomForest",
    -  response = "class",
    -  threshold = 0.05
    -)
    - -

    Arguments

    - - - - - - - - - - - - - - - - - - -
    organism

    KEGG organism ID

    model

    model type to use for extracting explanatory features

    response

    response variable name to use for extracting explanatory features

    threshold

    explanatory feature cutoff

    - - -
    - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/example_analysis.html b/docs/reference/example_analysis.html deleted file mode 100644 index 4d420cc..0000000 --- a/docs/reference/example_analysis.html +++ /dev/null @@ -1,159 +0,0 @@ - - - - - - - - -Example analysis data — example_analysis • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - -
    -

    Example analysis data

    -
    - -
    example_analysis
    - - -

    Format

    - -

    S4 object of class Analysis from the metabolyseR package.

    -

    Source

    - -

    Example analysis data based on the Brachypodium distachyon -ecotype comparison FIE-MS metabolomic fingerprinting data set available -in the metaboData package.

    - -
    - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/example_assignment.html b/docs/reference/example_assignment.html deleted file mode 100644 index 86d9ab0..0000000 --- a/docs/reference/example_assignment.html +++ /dev/null @@ -1,159 +0,0 @@ - - - - - - - - -Example molecular formula assignment data — example_assignment • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - -
    -

    Example molecular formula assignment data

    -
    - -
    example_assignment
    - - -

    Format

    - -

    S4 object of class Assignment from the MFassign package.

    -

    Source

    - -

    Example analysis data based on the Brachypodium distachyon -ecotype comparison FIE-MS metabolomic fingerprinting data set available -in the metaboData package.

    - -
    - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/functionalEnrichment.html b/docs/reference/functionalEnrichment.html deleted file mode 100644 index 4b8c16a..0000000 --- a/docs/reference/functionalEnrichment.html +++ /dev/null @@ -1,182 +0,0 @@ - - - - - - - - -functionalEnrichment — functionalEnrichment • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - -
    -

    Functional enrichment.

    -
    - -
    functionalEnrichment(analysis, assignment, parameters)
    -
    -# S4 method for Analysis,Assignment,EnrichmentParameters
    -functionalEnrichment(analysis, assignment, parameters)
    - -

    Arguments

    - - - - - - - - - - - - - - -
    analysis

    S4 object of class Analysis

    assignment

    S4 object of class Assignment

    parameters

    S4 object of class EnrichmentParameters

    - - -

    Examples

    -
    if (FALSE) { -## Generate enrichment parameters -parameters <- enrichmentParameters('bdi') - -## Select only "diffusion" enrichment -functional(parameters) <- list(methods = 'diffusion') - -## Run functional enrichment -fe <- functionalEnrichment(example_analysis,example_assignment,parameters) -} -
    -
    - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/index.html b/docs/reference/index.html deleted file mode 100644 index d59a712..0000000 --- a/docs/reference/index.html +++ /dev/null @@ -1,200 +0,0 @@ - - - - - - - - -Function reference • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -

    All functions

    -

    -
    -

    functional() `functional<-`()

    -

    Get and set enrichment parameters

    -

    enrichmentParameters()

    -

    enrichmentParameters

    -

    example_analysis

    -

    Example analysis data

    -

    example_assignment

    -

    Example molecular formula assignment data

    -

    functionalEnrichment()

    -

    functionalEnrichment

    -

    organismNetwork()

    -

    organismNetwork

    -
    - - -
    - - -
    - - -
    -

    Site built with pkgdown 1.6.1.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/reference/organismNetwork.html b/docs/reference/organismNetwork.html deleted file mode 100644 index 7911ee2..0000000 --- a/docs/reference/organismNetwork.html +++ /dev/null @@ -1,159 +0,0 @@ - - - - - - - - -organismNetwork — organismNetwork • riches - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -
    - - - - -
    - -
    -
    - - -
    -

    Gather organism specific KEGG network ready for enrichment analysis

    -
    - -
    organismNetwork(organism = "hsa")
    - -

    Arguments

    - - - - - - -
    organism

    KEGG organism code

    - - -
    - -
    - - - -
    - - - - - - - - diff --git a/inst/bdi/hypergeom.matrix.RData b/inst/bdi/hypergeom.matrix.RData new file mode 100644 index 0000000..5060750 Binary files /dev/null and b/inst/bdi/hypergeom.matrix.RData differ diff --git a/inst/bdi/keggdata.graph.RData b/inst/bdi/keggdata.graph.RData new file mode 100644 index 0000000..f35f9e7 Binary files /dev/null and b/inst/bdi/keggdata.graph.RData differ diff --git a/man/EnrichmentParameters-accessors.Rd b/man/EnrichmentParameters-accessors.Rd deleted file mode 100644 index 5f32a3f..0000000 --- a/man/EnrichmentParameters-accessors.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/allGenerics.R, R/access.R -\name{functional} -\alias{functional} -\alias{functional<-} -\alias{functional,EnrichmentParameters-method} -\alias{functional<-,EnrichmentParameters-method} -\title{Get and set enrichment parameters} -\usage{ -functional(x) - -functional(x) <- value - -\S4method{functional}{EnrichmentParameters}(x) - -\S4method{functional}{EnrichmentParameters}(x) <- value -} -\arguments{ -\item{x}{S4 object of class EnrichmentParameters} - -\item{value}{value to set} -} -\description{ -Retrieve or set enrichment parameters. -} diff --git a/man/assigned_data.Rd b/man/assigned_data.Rd new file mode 100644 index 0000000..1168920 --- /dev/null +++ b/man/assigned_data.Rd @@ -0,0 +1,22 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/assigned-data.R +\docType{data} +\name{assigned_data} +\alias{assigned_data} +\title{Example analysis data} +\format{ +S4 object of class AnalysisData from the metabolyseR package. +} +\source{ +Example analysis data based on the \emph{Brachypodium distachyon} +ecotype comparison FIE-MS metabolomic fingerprinting data set available +in the metaboData package. The features include putative molecular formula +assignments. +} +\usage{ +assigned_data +} +\description{ +Example analysis data +} +\keyword{datasets} diff --git a/man/availableMethods.Rd b/man/availableMethods.Rd new file mode 100644 index 0000000..fee458f --- /dev/null +++ b/man/availableMethods.Rd @@ -0,0 +1,17 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/functional-enrichment.R +\name{availableMethods} +\alias{availableMethods} +\title{Available functional enrichment methods} +\usage{ +availableMethods() +} +\value{ +A character vector of available methods. +} +\description{ +Methods available for functional enrichment using the FELLA package +} +\examples{ +availableMethods() +} diff --git a/man/enrichmentParameters.Rd b/man/enrichmentParameters.Rd deleted file mode 100644 index 9b33a95..0000000 --- a/man/enrichmentParameters.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/enrichmentParameters.R -\name{enrichmentParameters} -\alias{enrichmentParameters} -\title{enrichmentParameters} -\usage{ -enrichmentParameters( - organism, - model = "randomForest", - response = "class", - threshold = 0.05 -) -} -\arguments{ -\item{organism}{KEGG organism ID} - -\item{model}{model type to use for extracting explanatory features} - -\item{response}{response variable name to use for extracting explanatory features} - -\item{threshold}{explanatory feature cutoff} -} -\description{ -Enrichment parameters. -} diff --git a/man/example_analysis.Rd b/man/example_analysis.Rd deleted file mode 100644 index 0906d80..0000000 --- a/man/example_analysis.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/example-data.R -\docType{data} -\name{example_analysis} -\alias{example_analysis} -\title{Example analysis data} -\format{ -S4 object of class Analysis from the metabolyseR package. -} -\source{ -Example analysis data based on the Brachypodium distachyon -ecotype comparison FIE-MS metabolomic fingerprinting data set available -in the metaboData package. -} -\usage{ -example_analysis -} -\description{ -Example analysis data -} -\keyword{datasets} diff --git a/man/example_assignment.Rd b/man/example_assignment.Rd deleted file mode 100644 index 72b38dd..0000000 --- a/man/example_assignment.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/example-data.R -\docType{data} -\name{example_assignment} -\alias{example_assignment} -\title{Example molecular formula assignment data} -\format{ -S4 object of class Assignment from the MFassign package. -} -\source{ -Example analysis data based on the Brachypodium distachyon -ecotype comparison FIE-MS metabolomic fingerprinting data set available -in the metaboData package. -} -\usage{ -example_assignment -} -\description{ -Example molecular formula assignment data -} -\keyword{datasets} diff --git a/man/functional-accessors.Rd b/man/functional-accessors.Rd new file mode 100644 index 0000000..73749f2 --- /dev/null +++ b/man/functional-accessors.Rd @@ -0,0 +1,74 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/functional-enrichment.R +\name{hits} +\alias{hits} +\alias{hits,FunctionalEnrichment-method} +\alias{explanatoryFeatures,FunctionalEnrichment-method} +\alias{enrichmentResults} +\alias{enrichmentResults,FunctionalEnrichment-method} +\alias{generateResultsTable} +\alias{generateResultsTable,FunctionalEnrichment-method} +\title{FunctionalEnrichment S4 class accessors} +\usage{ +hits(x) + +\S4method{hits}{FunctionalEnrichment}(x) + +\S4method{explanatoryFeatures}{FunctionalEnrichment}(x) + +enrichmentResults(x) + +\S4method{enrichmentResults}{FunctionalEnrichment}(x) + +generateResultsTable(x, method = availableMethods(), nlimit = 250, ...) + +\S4method{generateResultsTable}{FunctionalEnrichment}(x, method = availableMethods(), nlimit = 250) +} +\arguments{ +\item{x}{object of S4 class \code{FunctionalEnrichment}} + +\item{method}{the method results to access. One of \code{availableMethods}.} + +\item{nlimit}{argument to pass to argument \code{nlimit} of \code{FELLA::generateResultsTable}. Limits the order of the sub-graph solutions for methods \code{diffusion} and \code{pagerank}.} + +\item{...}{ignored} +} +\value{ +A tibble or a list of objects of \code{FELLA.USER} S4 class depending on the method used. +} +\description{ +Accessor methods for the \code{FunctionalEnrichment} S4 class. +} +\examples{ +## Perform random forest on the example data +random_forest <- assigned_data \%>\% +metabolyseR::randomForest( + cls = 'class' +) + +## Perform functional enrichment analysis +enrichment_results <- functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ) +) + +## Access the m/z feature KEGG compound matches +hits(enrichment_results) + +## Access the explanatory features used for functional enrichment +explanatoryFeatures(enrichment_results) + +## Access the FELLA.USER functional enrichment object +enrichmentResults(enrichment_results) + +## Extract a table of enrichment results +generateResultsTable(enrichment_results) +} diff --git a/man/functionalEnrichment.Rd b/man/functionalEnrichment.Rd index 2629542..42be3a8 100644 --- a/man/functionalEnrichment.Rd +++ b/man/functionalEnrichment.Rd @@ -1,33 +1,109 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/allGenerics.R, R/functionalEnrichment.R +% Please edit documentation in R/functional-enrichment.R \name{functionalEnrichment} \alias{functionalEnrichment} -\alias{functionalEnrichment,Analysis,Assignment,EnrichmentParameters-method} -\title{functionalEnrichment} +\alias{functionalEnrichment,RandomForest-method} +\title{Functional enrichment} \usage{ -functionalEnrichment(analysis, assignment, parameters) +functionalEnrichment( + x, + organism, + methods = availableMethods(), + split = c("none", "trends"), + organism_data = organismData(organism), + adduct_rules_table = adduct_rules(), + ... +) -\S4method{functionalEnrichment}{Analysis,Assignment,EnrichmentParameters}(analysis, assignment, parameters) +\S4method{functionalEnrichment}{RandomForest}( + x, + organism, + methods = availableMethods(), + split = c("none", "trends"), + organism_data = organismData(organism), + adduct_rules_table = adduct_rules(), + ... +) } \arguments{ -\item{analysis}{S4 object of class Analysis} +\item{x}{object of S4 class \code{RandomForest}} -\item{assignment}{S4 object of class Assignment} +\item{organism}{the KEGG code for the organism of interest} -\item{parameters}{S4 object of class EnrichmentParameters} +\item{methods}{the enrichment techniques to build. Any returned by \code{availableMethods}.} + +\item{split}{split the explanatory features into further groups based on their trends. See details.} + +\item{organism_data}{an object of S4 class \code{FELLA.DATA}} + +\item{adduct_rules_table}{the adduct ionisation rules for matching m/z features to KEGG compounds. +Format should be as returned from \code{mzAnnotation::adduct_rules}.} + +\item{...}{arguments to pass to \code{metabolyseR::explanatoryFeatures}} +} +\value{ +An object of S4 class \code{FunctionalEnrichment}. } \description{ -Functional enrichment. +Perform functional enrichment analyses of explanatory features using the +\href{https://bioconductor.org/packages/release/bioc/html/FELLA.html}{{FELLA}} R package. } -\examples{ -\dontrun{ -## Generate enrichment parameters -parameters <- enrichmentParameters('bdi') +\details{ +For argument \code{split = 'trends'}, the explanatory features can be split into further groups +based on their trends. This is not supported for unsupervised random forest. -## Select only "diffusion" enrichment -functional(parameters) <- list(methods = 'diffusion') +For random forest classification, this is for binary comparisons only. Functional enrichment +is performed seperately on the up and down regulated explanatory features for each comparison. The +\verb{up regulated} and \verb{down regulated} groups are based on the trends of log2 ratios between +the comparison classes. \verb{up regulated} explanatory features have a higher median intensity +in the right-hand class compared to the left-hand class of the comparison. The opposite is true +for the \verb{down regulated} explanatory features. -## Run functional enrichment -fe <- functionalEnrichment(example_analysis,example_assignment,parameters) +For random forest regression, the explanatory features are split based on their Spearman's +correlation coefficient with the response variable prior to functional enrichment analysis +giving \verb{positively correlated} and \verb{negatively correlated} subgroups. } +\examples{ +## Perform random forest on the example data +random_forest <- assigned_data \%>\% +metabolyseR::randomForest( + cls = 'class' +) + +## Perform functional enrichment analysis +functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ) +) + +## An example using split trends +## Perform binary random forest classification on the example data +random_forest <- assigned_data \%>\% + metabolyseR::randomForest( + cls = 'class', + binary = TRUE + ) + +## Perform functional enrichment analysis +functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + split = 'trends', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ) +) } diff --git a/man/organismData.Rd b/man/organismData.Rd new file mode 100644 index 0000000..15f866d --- /dev/null +++ b/man/organismData.Rd @@ -0,0 +1,49 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/organism-data.R +\name{organismData} +\alias{organismData} +\title{Organism data} +\usage{ +organismData( + organism, + methods = availableMethods(), + filter_path = NULL, + database_directory = organism, + internal_directory = TRUE, + damping_factor = 0.85, + niter = 100 +) +} +\arguments{ +\item{organism}{the KEGG code for the organism of interest} + +\item{methods}{the enrichment techniques to build. Any returned by \code{availableMethods}.} + +\item{filter_path}{argument to pass to argument \code{filter.path} of \code{FELLA::buildGraphFromKEGGREST}. A vector of regular expressions to match pathways to exclude.} + +\item{database_directory}{argument to pass to argument \code{databaseDir} of \code{FELLA::buildDataFromGraph} and \code{FELLA::loadKEGGdata}. The directory name/path in which to save the KEGG data.} + +\item{internal_directory}{logical. Argument to pass to argument \code{internalDir} of \code{FELLA::buildDataFromGraph} and \code{FELLA::loadKEGGdata}. Should the save directory be internal to the FELLA package directory?} + +\item{damping_factor}{argument to pass to argument \code{dampingFactor} of \code{FELLA::buildDataFromGraph}. A value between 0 and 1 for the PageRank damping factor.} + +\item{niter}{argument to pass to argument \code{niter} of \code{FELLA::buildDataFromGraph}. A value between 10 and 1000. The number of iterations to estimate the values for CC size.} +} +\value{ +An object of S4 class \code{FELLA.DATA} containing the KEGG data for the specified organism. +} +\description{ +Load or build the organism specific KEGG datafor enrichment analysis. +This provides a convenience wrapper around \code{FELLA::loadKEGGdata}, \code{FELLA::buildGraphFromKEGGREST} and +\code{FELLA::buildDataFromGraph}. See the documentation of these functions for further information. +} +\examples{ +## Load the example organism data available from within the package +organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE +) +} diff --git a/man/organismNetwork.Rd b/man/organismNetwork.Rd deleted file mode 100644 index e87a63d..0000000 --- a/man/organismNetwork.Rd +++ /dev/null @@ -1,14 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/organismNetwork.R -\name{organismNetwork} -\alias{organismNetwork} -\title{organismNetwork} -\usage{ -organismNetwork(organism = "hsa") -} -\arguments{ -\item{organism}{KEGG organism code} -} -\description{ -Gather organism specific KEGG network ready for enrichment analysis -} diff --git a/man/reexports.Rd b/man/reexports.Rd new file mode 100644 index 0000000..d02102e --- /dev/null +++ b/man/reexports.Rd @@ -0,0 +1,16 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/reexports.R +\docType{import} +\name{reexports} +\alias{reexports} +\alias{\%>\%} +\title{Objects exported from other packages} +\keyword{internal} +\description{ +These objects are imported from other packages. Follow the links +below to see their documentation. + +\describe{ + \item{magrittr}{\code{\link[magrittr:pipe]{\%>\%}}} +}} + diff --git a/man/structural-accessors.Rd b/man/structural-accessors.Rd new file mode 100644 index 0000000..ec226fd --- /dev/null +++ b/man/structural-accessors.Rd @@ -0,0 +1,48 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/structural-enrichment.R +\name{structuralClassifications} +\alias{structuralClassifications} +\alias{structuralClassifications,StructuralEnrichment-method} +\alias{explanatoryFeatures,StructuralEnrichment-method} +\alias{enrichmentResults,StructuralEnrichment-method} +\title{StructuralEnrichment S4 class accessors} +\usage{ +structuralClassifications(x) + +\S4method{structuralClassifications}{StructuralEnrichment}(x) + +\S4method{explanatoryFeatures}{StructuralEnrichment}(x) + +\S4method{enrichmentResults}{StructuralEnrichment}(x) +} +\arguments{ +\item{x}{object of S4 class \code{StructuralEnrichment}} +} +\value{ +A tibble containing the accessed information. +} +\description{ +Accessor methods for the \code{StructuralEnrichment} S4 class. +} +\examples{ +## Perform random forest on the example data +random_forest <- assigned_data \%>\% + metabolyseR::randomForest( + cls = 'class' + ) + +## Perform functional enrichment analysis +enrichment_results <- structuralEnrichment( + random_forest, + structural_classifications +) + +## The m/z feature structural classifcations +structuralClassifications(enrichment_results) + +## Access the explanatory features used for structural enrichment analysis +explanatoryFeatures(enrichment_results) + +## Access the structral enrichment analysis results +enrichmentResults(enrichment_results) +} diff --git a/man/structuralEnrichment.Rd b/man/structuralEnrichment.Rd new file mode 100644 index 0000000..e522ba9 --- /dev/null +++ b/man/structuralEnrichment.Rd @@ -0,0 +1,95 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/structural-enrichment.R +\name{structuralEnrichment} +\alias{structuralEnrichment} +\alias{structuralEnrichment,RandomForest,tbl_df-method} +\alias{structuralEnrichment,RandomForest,Construction-method} +\title{Structural enrichment} +\usage{ +structuralEnrichment( + x, + structural_classifications, + p_adjust_method = "bonferroni", + split = c("none", "trends"), + ... +) + +\S4method{structuralEnrichment}{RandomForest,tbl_df}( + x, + structural_classifications, + p_adjust_method = "bonferroni", + split = c("none", "trends"), + ... +) + +\S4method{structuralEnrichment}{RandomForest,Construction}( + x, + structural_classifications, + p_adjust_method = "bonferroni", + split = c("none", "trends"), + ... +) +} +\arguments{ +\item{x}{an object of S4 class \code{RandomForest}} + +\item{structural_classifications}{the structral classifications corresponding to the \emph{m/z} features present in the object specified for argument \code{x}. This should either be a tibble as returned by \code{construction::classifications()} or an object of S4 class \code{Construction}.} + +\item{p_adjust_method}{the p-value adjustment method. One of those returned from \code{p.adjust.methods}.} + +\item{split}{split the explanatory features into further groups based on their trends. See details.} + +\item{...}{arguments to pass to \code{metabolyseR::explanatoryFeatures()}} +} +\value{ +An object of S4 class \code{StructuralEnrichment}. +} +\description{ +Perform structural enrichment using over-representation analysis of explanatory \emph{m/z} features from random forest. +} +\details{ +Over-representation analysis is performed on the explanatory \emph{m/z} features for each structural class +within each experimental class comparison using the Fisher's Exact Test. + +For argument \code{split = 'trends'}, the explanatory features can be split into further groups +based on their trends. This is not supported for unsupervised random forest. + +For random forest classification, this is for binary comparisons only. Functional enrichment +is performed seperately on the up and down regulated explanatory features for each comparison. The +\verb{up regulated} and \verb{down regulated} groups are based on the trends of log2 ratios between +the comparison classes. \verb{up regulated} explanatory features have a higher median intensity +in the right-hand class compared to the left-hand class of the comparison. The opposite is true +for the \verb{down regulated} explanatory features. + +For random forest regression, the explanatory features are split based on their Spearman's +correlation coefficient with the response variable prior to functional enrichment analysis +giving \verb{positively correlated} and \verb{negatively correlated} subgroups. +} +\examples{ +## Perform random forest on the example data +random_forest <- assigned_data \%>\% + metabolyseR::randomForest( + cls = 'class' + ) + +## Perform structural enrichment analysis using the example structural classifications +structuralEnrichment( + random_forest, + structural_classifications +) + +## An example using split trends +## Perform random forest on the example data +random_forest <- assigned_data \%>\% + metabolyseR::randomForest( + cls = 'class', + binary = TRUE + ) + +## Perform structural enrichment analysis using the example structural classifications +structuralEnrichment( + random_forest, + structural_classifications, + split = 'trends' +) +} diff --git a/man/structural_classifications.Rd b/man/structural_classifications.Rd new file mode 100644 index 0000000..ca14ccd --- /dev/null +++ b/man/structural_classifications.Rd @@ -0,0 +1,24 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/structural-classifications.R +\docType{data} +\name{structural_classifications} +\alias{structural_classifications} +\title{Example structural classifications} +\format{ +A tibble containing consensus structural classifications for the \emph{m/z} features found +in the \code{assigned_data} example data set. +} +\source{ +These example consensus structural classifications were generated using the +\href{https://jasenfinch.github.io/construction/}{{construction}} package (v0.3.0) and are based on +the example analysis data (\code{assigned_data}) based on the \emph{Brachypodium distachyon} ecotype +comparison FIE-MS metabolomic fingerprinting data set available in the +\href{https://aberhrml.github.io/metaboData/}{{metaboData}} package. +} +\usage{ +structural_classifications +} +\description{ +Example structural classifications +} +\keyword{datasets} diff --git a/tests/testthat/test-functional-enrichment.R b/tests/testthat/test-functional-enrichment.R index 63d0e79..b9b9c94 100644 --- a/tests/testthat/test-functional-enrichment.R +++ b/tests/testthat/test-functional-enrichment.R @@ -1,11 +1,128 @@ -context('functional enrichment') +test_that('functional enrichment works for random forest classification',{ + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = 'class', + comparisons = list( + class = 'ABR1~BD21' + )) + + enrichment_results <- functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ), + split = 'trends' + ) + + expect_s4_class(enrichment_results,'FunctionalEnrichment') + expect_s3_class(hits(enrichment_results),'tbl_df') + expect_s3_class(explanatoryFeatures(enrichment_results),'tbl_df') + expect_type(enrichmentResults(enrichment_results),'list') + expect_s3_class(generateResultsTable(enrichment_results),'tbl_df') + expect_output(show(enrichment_results),'Random forest') +}) + +test_that('functional enrichment works for random forest regression',{ + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = 'injOrder' + ) + + enrichment_results <- functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ), + split = 'trends', + metric = '%IncMSE' + ) + + expect_s4_class(enrichment_results,'FunctionalEnrichment') + expect_s3_class(hits(enrichment_results),'tbl_df') + expect_s3_class(explanatoryFeatures(enrichment_results),'tbl_df') + expect_type(enrichmentResults(enrichment_results),'list') + expect_s3_class(generateResultsTable(enrichment_results),'tbl_df') + expect_output(show(enrichment_results),'Random forest') +}) -test_that('functional enrichment works',{ - parameters <- enrichmentParameters('bdi') - functional(parameters) <- list(methods = 'diffusion') +test_that('functional enrichment works for unsupervised random forest',{ + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = NULL + ) - fe <- functionalEnrichment(example_analysis,example_assignment,parameters) + enrichment_results <- functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ) + ) + + expect_s4_class(enrichment_results,'FunctionalEnrichment') + expect_s3_class(hits(enrichment_results),'tbl_df') + expect_s3_class(explanatoryFeatures(enrichment_results),'tbl_df') + expect_type(enrichmentResults(enrichment_results),'list') + expect_s3_class(generateResultsTable(enrichment_results),'tbl_df') + expect_output(show(enrichment_results),'Unsupervised') +}) + +test_that('functional enrichment errors if no binary comparisons are found for trends for unsupervised random forest',{ + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = 'class' + ) + + expect_warning(expect_error(functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ), + split = 'trends') + )) +}) + +test_that('functional enrichment errors with trends for unsupervised random forest',{ + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = NULL + ) - expect_s4_class(fe,'FunctionalEnrichment') -}) \ No newline at end of file + expect_error(functionalEnrichment( + random_forest, + 'bdi', + methods = 'hypergeom', + organism_data = organismData( + 'bdi', + database_directory = system.file( + 'bdi', + package = 'riches'), + internal_directory = FALSE + ), + split = 'trends') + ) +}) diff --git a/tests/testthat/test-organism-data.R b/tests/testthat/test-organism-data.R new file mode 100644 index 0000000..f1b86c7 --- /dev/null +++ b/tests/testthat/test-organism-data.R @@ -0,0 +1,24 @@ + +test_that("organism data can be loaded", { + data_path <- system.file('bdi', + package = 'riches') + organism_data <- organismData( + 'bdi', + database_directory = data_path, + internal_directory = FALSE) + + expect_s4_class(organism_data,'FELLA.DATA') +}) + +test_that('organism compounds can be extracted',{ + data_path <- system.file('bdi', + package = 'riches') + organism_data <- organismData( + 'bdi', + database_directory = data_path, + internal_directory = FALSE) + + organism_compounds <- organismCompounds(organism_data) + + expect_s3_class(organism_compounds,'tbl_df') +}) \ No newline at end of file diff --git a/tests/testthat/test-structural-enrichment.R b/tests/testthat/test-structural-enrichment.R new file mode 100644 index 0000000..d49bb23 --- /dev/null +++ b/tests/testthat/test-structural-enrichment.R @@ -0,0 +1,51 @@ + +test_that("structural enrichment works for random forest classification", { + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = 'class', + comparisons = list( + class = 'ABR1~BD21' + ) + ) + + structural_enrichment <- structuralEnrichment( + random_forest, + structural_classifications, + split = 'trends' + ) + + expect_s4_class(structural_enrichment,'StructuralEnrichment') + expect_output(show(structural_enrichment),'Random forest') +}) + +test_that("structural enrichment works for random forest regression", { + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = 'injOrder' + ) + + structural_enrichment <- structuralEnrichment( + random_forest, + structural_classifications, + split = 'trends', + metric = '%IncMSE' + ) + + expect_s4_class(structural_enrichment,'StructuralEnrichment') + expect_output(show(structural_enrichment),'Random forest') +}) + +test_that("structural enrichment works for unsupervised random forest", { + random_forest <- assigned_data %>% + metabolyseR::randomForest( + cls = NULL + ) + + structural_enrichment <- structuralEnrichment( + random_forest, + structural_classifications + ) + + expect_s4_class(structural_enrichment,'StructuralEnrichment') + expect_output(show(structural_enrichment),'Unsupervised') +})