Merge devel

microbiome · Apr 10, 2024 · b162c51 · b162c51
2 parents 0ba5bd1 + 1d01162
commit b162c51
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Showing 9 changed files with 177 additions and 142 deletions.
diff --git a/NAMESPACE b/NAMESPACE
@@ -3,6 +3,7 @@
 export(IdTaxaToDataFrame)
 export(TAXONOMY_RANKS)
 export(ZTransform)
+export(addCluster)
 export(addContaminantQC)
 export(addNotContaminantQC)
 export(addPerSampleDominantFeatures)
@@ -17,7 +18,6 @@ export(calculateJSD)
 export(calculateNMDS)
 export(calculateOverlap)
 export(calculateUnifrac)
-export(cluster)
 export(countDominantFeatures)
 export(countDominantTaxa)
 export(estimateDivergence)
@@ -100,6 +100,7 @@ export(unsplitByRanks)
 export(unsplitOn)
 exportMethods("relabundance<-")
 exportMethods(ZTransform)
+exportMethods(addCluster)
 exportMethods(addContaminantQC)
 exportMethods(addHierarchyTree)
 exportMethods(addNotContaminantQC)

diff --git a/NEWS b/NEWS
@@ -105,3 +105,4 @@ Changes in version 1.11.x
 + getPrevalence: bugfix, if assay contains NA values, it does not end up to NA anymore.
 + getExperimentCrossCorrelation fix: enable using of sampleMap in MAE.
 + Implemented the setTaxonomyRanks function to specify which ranks are recognized as taxonomy ranks.
++ Rename cluster to addCluster
diff --git a/R/calculateDMM.R b/R/calculateDMM.R
@@ -104,20 +104,20 @@ NULL
 #' @rdname calculateDMN
 #' @export
 setGeneric("calculateDMN", signature = c("x"),
-           function(x, ...)
-               standardGeneric("calculateDMN"))
+    function(x, ...)
+            standardGeneric("calculateDMN"))
 
 #' @importFrom DirichletMultinomial dmn
 #' @importFrom stats runif
 .calculate_DMN <- function(x, k = 1, BPPARAM = SerialParam(),
-                           seed = runif(1, 0, .Machine$integer.max), ...){
+                            seed = runif(1, 0, .Machine$integer.max), ...){
     if(!is.numeric(k) ||
-       length(k) == 0 ||
-       anyNA(k) ||
-       any(k <= 0) ||
-       any(k != as.integer(k))){
+        length(k) == 0 ||
+        anyNA(k) ||
+        any(k <= 0) ||
+        any(k != as.integer(k))){
         stop("'k' must be an integer vector with positive values only.",
-             call. = FALSE)
+            call. = FALSE)
     }
     #
     old <- getAutoBPPARAM()
@@ -127,10 +127,10 @@ setGeneric("calculateDMN", signature = c("x"),
         bpstart(BPPARAM)
         on.exit(bpstop(BPPARAM), add = TRUE)
     }
-
+    
     ans <- BiocParallel::bplapply(k, DirichletMultinomial::dmn, count = x,
-                                  seed = seed, ...,
-                                  BPPARAM = BPPARAM)
+                                    seed = seed, ...,
+                                    BPPARAM = BPPARAM)
     ans
 }
 
@@ -141,10 +141,11 @@ setMethod("calculateDMN", signature = c(x = "ANY"), .calculate_DMN)
 #' @rdname calculateDMN
 #' @export
 setMethod("calculateDMN", signature = c(x = "SummarizedExperiment"),
-    function(x, assay.type = assay_name, assay_name = exprs_values, exprs_values = "counts", 
-             transposed = FALSE, ...){
+    function(x, assay.type = assay_name, assay_name = exprs_values,
+            exprs_values = "counts", transposed = FALSE, ...){
         .Deprecated(old="calculateDMN", new="cluster", 
-                    "Now calculateDMN is deprecated. Use cluster with DMMParam parameter instead.")
+                    "Now calculateDMN is deprecated. 
+                    Use cluster with DMMParam parameter instead.")
         mat <- assay(x, assay.type)
         if(!transposed){
             mat <- t(mat)
@@ -158,7 +159,8 @@ setMethod("calculateDMN", signature = c(x = "SummarizedExperiment"),
 #' @export
 runDMN <- function(x, name = "DMN", ...){
     .Deprecated(old="runDMN", new="cluster", 
-                "Now runDMN is deprecated. Use cluster with DMMParam parameter instead.")
+                "Now runDMN is deprecated. 
+                Use cluster with DMMParam parameter instead.")
     if(!is(x,"SummarizedExperiment")){
         stop("'x' must be a SummarizedExperiment")
     }
@@ -185,27 +187,29 @@ runDMN <- function(x, name = "DMN", ...){
 .get_dmn_fit_FUN <- function(type){
     type <- match.arg(type, c("laplace","AIC","BIC"))
     fit_FUN <- switch(type,
-                      laplace = DirichletMultinomial::laplace,
-                      AIC = DirichletMultinomial::AIC,
-                      BIC = DirichletMultinomial::BIC)
+                        laplace = DirichletMultinomial::laplace,
+                        AIC = DirichletMultinomial::AIC,
+                        BIC = DirichletMultinomial::BIC)
     fit_FUN
 }
 
 #' @rdname calculateDMN
 #' @export
 setGeneric("getDMN", signature = "x",
-           function(x, name = "DMN", ...)
-               standardGeneric("getDMN"))
+            function(x, name = "DMN", ...)
+                standardGeneric("getDMN"))
 
 #' @rdname calculateDMN
 #' @importFrom DirichletMultinomial laplace AIC BIC
 #' @export
 setMethod("getDMN", signature = c(x = "SummarizedExperiment"),
-    function(x, name = "DMN"){
-        .Deprecated(old="getDMN", new="cluster", 
-                    "Now getDMN is deprecated. Use cluster with DMMParam parameter and full parameter set as true instead.")
-        .get_dmn(x, name)
-    }
+            function(x, name = "DMN"){
+                .Deprecated(old="getDMN", new="cluster", 
+                            "Now getDMN is deprecated. 
+                            Use cluster with DMMParam parameter 
+                            and full parameter set as true instead.")
+                .get_dmn(x, name)
+            }
 )
 
 
@@ -217,41 +221,45 @@ setMethod("getDMN", signature = c(x = "SummarizedExperiment"),
 #' @rdname calculateDMN
 #' @export
 setGeneric("bestDMNFit", signature = "x",
-           function(x, name = "DMN", type = c("laplace","AIC","BIC"), ...)
-               standardGeneric("bestDMNFit"))
+            function(x, name = "DMN", type = c("laplace","AIC","BIC"), ...)
+                standardGeneric("bestDMNFit"))
 
 #' @rdname calculateDMN
 #' @importFrom DirichletMultinomial laplace AIC BIC
 #' @export
 setMethod("bestDMNFit", signature = c(x = "SummarizedExperiment"),
-    function(x, name = "DMN", type = c("laplace","AIC","BIC")){
-        .Deprecated(old="bestDMNFit", new="cluster", 
-                    "Now bestDMNFit is deprecated. Use cluster with DMMParam parameter and full parameter set as true instead.")
-        #
-        dmn <- getDMN(x, name)
-        fit_FUN <- .get_dmn_fit_FUN(type)
-        #
-        .get_best_dmn_fit(dmn, fit_FUN)
-    }
+            function(x, name = "DMN", type = c("laplace","AIC","BIC")){
+                .Deprecated(old="bestDMNFit", new="cluster", 
+                            "Now bestDMNFit is deprecated.
+                            Use cluster with DMMParam parameter 
+                            and full parameter set as true instead.")
+                #
+                dmn <- getDMN(x, name)
+                fit_FUN <- .get_dmn_fit_FUN(type)
+                #
+                .get_best_dmn_fit(dmn, fit_FUN)
+            }
 )
 
 #' @rdname calculateDMN
 #' @export
 setGeneric("getBestDMNFit", signature = "x",
-           function(x, name = "DMN", type = c("laplace","AIC","BIC"), ...)
-               standardGeneric("getBestDMNFit"))
+            function(x, name = "DMN", type = c("laplace","AIC","BIC"), ...)
+                standardGeneric("getBestDMNFit"))
 
 #' @rdname calculateDMN
 #' @importFrom DirichletMultinomial laplace AIC BIC
 #' @export
 setMethod("getBestDMNFit", signature = c(x = "SummarizedExperiment"),
-    function(x, name = "DMN", type = c("laplace","AIC","BIC")){
-        .Deprecated(old="getBestDMNFit", new="cluster", 
-                    "Now getBestDMNFit is deprecated. Use cluster with DMMParam parameter and full parameter set as true instead.")
-        dmn <- getDMN(x, name)
-        fit_FUN <- .get_dmn_fit_FUN(type)
-        dmn[[.get_best_dmn_fit(dmn, fit_FUN)]]
-    }
+            function(x, name = "DMN", type = c("laplace","AIC","BIC")){
+                .Deprecated(old="getBestDMNFit", new="cluster", 
+                            "Now getBestDMNFit is deprecated. 
+                            Use cluster with DMMParam parameter 
+                            and full parameter set as true instead.")
+                dmn <- getDMN(x, name)
+                fit_FUN <- .get_dmn_fit_FUN(type)
+                dmn[[.get_best_dmn_fit(dmn, fit_FUN)]]
+            }
 )
 
 ################################################################################
@@ -260,8 +268,8 @@ setMethod("getBestDMNFit", signature = c(x = "SummarizedExperiment"),
 #' @rdname calculateDMN
 #' @export
 setGeneric("calculateDMNgroup", signature = c("x"),
-           function(x, ...)
-               standardGeneric("calculateDMNgroup"))
+            function(x, ...)
+                standardGeneric("calculateDMNgroup"))
 
 #' @importFrom DirichletMultinomial dmngroup
 #' @importFrom stats runif
@@ -285,20 +293,20 @@ setMethod("calculateDMNgroup", signature = c(x = "ANY"), .calculate_DMNgroup)
 #' @rdname calculateDMN
 #' @export
 setMethod("calculateDMNgroup", signature = c(x = "SummarizedExperiment"),
-    function(x, variable, 
-             assay.type = assay_name, assay_name = exprs_values, exprs_values = "counts", 
-             transposed = FALSE, ...){
-        mat <- assay(x, assay.type)
-        if(!transposed){
-            mat <- t(mat)
-        }
-        variable <- colData(x)[,variable]
-        if(is.null(variable)){
-            stop("No data found in '",variable,"' column of colData(x).",
-                 call. = FALSE)
-        }
-        calculateDMNgroup(x = mat, variable = variable, ...)
-    }
+            function(x, variable, 
+                    assay.type = assay_name, assay_name = exprs_values, 
+                    exprs_values = "counts", transposed = FALSE, ...){
+                mat <- assay(x, assay.type)
+                if(!transposed){
+                    mat <- t(mat)
+                }
+                variable <- colData(x)[,variable]
+                if(is.null(variable)){
+                    stop("No data found in '",variable,
+                        "' column of colData(x).", call. = FALSE)
+                }
+                calculateDMNgroup(x = mat, variable = variable, ...)
+            }
 )
 
 ################################################################################
@@ -307,13 +315,13 @@ setMethod("calculateDMNgroup", signature = c(x = "SummarizedExperiment"),
 #' @rdname calculateDMN
 #' @export
 setGeneric("performDMNgroupCV", signature = c("x"),
-           function(x, ...)
-               standardGeneric("performDMNgroupCV"))
+            function(x, ...)
+                standardGeneric("performDMNgroupCV"))
 
 #' @importFrom DirichletMultinomial cvdmngroup
 #' @importFrom stats runif
 .perform_DMNgroup_cv <- function(x, variable, k = 1,
-                                 seed = runif(1, 0, .Machine$integer.max), ...){
+                                seed = runif(1, 0, .Machine$integer.max), ...){
     # input check
     if(!is.factor(variable) && is.character(variable)){
         variable <- factor(variable, unique(variable))
@@ -323,7 +331,7 @@ setGeneric("performDMNgroupCV", signature = c("x"),
     variable <- droplevels(variable)
     if(is.null(names(k)) || !all(names(k) %in% levels(variable))){
         stop("'k' must be named. Names must fit the levels of 'variable'.",
-             call. = FALSE)
+            call. = FALSE)
     }
     #
     cvdmngroup(nrow(x), x, variable, k = k, seed = seed, ...)
@@ -336,18 +344,18 @@ setMethod("performDMNgroupCV", signature = c(x = "ANY"), .perform_DMNgroup_cv)
 #' @rdname calculateDMN
 #' @export
 setMethod("performDMNgroupCV", signature = c(x = "SummarizedExperiment"),
-    function(x, variable, 
-             assay.type = assay_name, assay_name = exprs_values, exprs_values = "counts", 
-             transposed = FALSE, ...){
-        mat <- assay(x, assay.type)
-        if(!transposed){
-            mat <- t(mat)
-        }
-        variable <- colData(x)[,variable]
-        if(is.null(variable)){
-            stop("No data found in '",variable,"' column of colData(x).",
-                 call. = FALSE)
-        }
-        performDMNgroupCV(x = mat, variable = variable, ...)
-    }
+            function(x, variable, 
+                    assay.type = assay_name, assay_name = exprs_values, 
+                    exprs_values = "counts", transposed = FALSE, ...){
+                mat <- assay(x, assay.type)
+                if(!transposed){
+                    mat <- t(mat)
+                }
+                variable <- colData(x)[,variable]
+                if(is.null(variable)){
+                    stop("No data found in '",variable,
+                        "' column of colData(x).", call. = FALSE)
+                }
+                performDMNgroupCV(x = mat, variable = variable, ...)
+            }
 )
diff --git a/R/cluster.R b/R/cluster.R
@@ -27,11 +27,11 @@
 #' By default, clustering is done on the features.
 #'
 #' @return
-#' \code{cluster} returns an object of the same type as the \code{x} parameter 
+#' \code{addCluster} returns an object of the same type as the \code{x} parameter 
 #' with clustering information named \code{clusters} stored in \code{colData} 
 #' or \code{rowData}. 
 #'
-#' @name cluster
+#' @name addCluster
 #' @export
 #' 
 #' @author Basil Courbayre
@@ -42,10 +42,10 @@
 #' tse <- GlobalPatterns
 #'
 #' # Cluster on rows using Kmeans
-#' tse <- cluster(tse, KmeansParam(centers = 3))
+#' tse <- addCluster(tse, KmeansParam(centers = 3))
 #' 
 #' # Clustering done on the samples using Hclust
-#' tse <- cluster(tse, 
+#' tse <- addCluster(tse, 
 #'                MARGIN = "samples", 
 #'                HclustParam(metric = "bray", dist.fun = vegan::vegdist))
 #' 
@@ -54,19 +54,20 @@
 #' 
 NULL
 
-#' @rdname cluster
+#' @rdname addCluster
 #' @export
-setGeneric("cluster", signature = c("x"),
+setGeneric("addCluster", signature = c("x"),
     function(
             x, BLUSPARAM, assay.type = assay_name, 
             assay_name = "counts", MARGIN = "features", full = FALSE, 
             name = "clusters", clust.col = "clusters", ...)
-    standardGeneric("cluster"))
+    standardGeneric("addCluster"))
 
-#' @rdname cluster
+
+#' @rdname addCluster
 #' @export
 #' @importFrom bluster clusterRows
-setMethod("cluster", signature = c(x = "SummarizedExperiment"),
+setMethod("addCluster", signature = c(x = "SummarizedExperiment"),
     function(
             x, BLUSPARAM, assay.type = assay_name, 
             assay_name = "counts", MARGIN = "features", full = FALSE,