Update to the version 1.0.5

DESCRIPTION

@@ -2,14 +2,14 @@ Package: dcGOR
 Type: Package
 Title: Analysis of Ontologies and Protein Domain Annotations
 Version: 1.0.5
-Date: 2015-7-20
+Date: 2015-7-22
 Author: Hai Fang and Julian Gough
 Maintainer: Hai Fang <hfang@well.ox.ac.uk>
 Depends: R (>= 3.1.0), Matrix, igraph, dnet
 Imports: methods
 Suggests: foreach, doMC, ape
 Description: There lacks a package for analysing domain-centric ontologies and annotations, particularly those in the dcGO database. The dcGO (http://supfam.org/SUPERFAMILY/dcGO) is a comprehensive domain-centric database for annotating protein domains using a panel of ontologies including Gene Ontology. With the package, users are expected to analyse and visualise domain-centric ontologies and annotations. Supported analyses include but are not limited to: easy access to a wide range of ontologies and their domain-centric annotations; able to build customised ontologies and annotations; domain-based enrichment analysis and visualisation; construction of a domain (semantic similarity) network according to ontology annotations; significance analysis for estimating a contact (statistical significance) network via Random Walk with Restart; and high-performance parallel computing. The new functionalities are: 1) to create domain-centric ontologies; 2) to predict ontology terms for input protein sequences (precisely domain content in the form of architectures) plus to assess the predictions; 3) to reconstruct ancestral discrete characters using maximum likelihood/parsimony.
-URL: http://supfam.org/dcGOR, http://dcgor.r-forge.r-project.org, http://cran.r-project.org/package=dcGOR, https://github.com/hfang-bristol/dcGOR
+URL: http://supfam.org/dcGOR, http://cran.r-project.org/package=dcGOR, http://dcgor.r-forge.r-project.org, https://github.com/hfang-bristol/dcGOR
 Collate: 
     'ClassMethod-dcGOR.r'
     'dcDAGannotate.r'

R/dcAlgo.r

@@ -14,7 +14,7 @@
 #' @param multicores an integer to specify how many cores will be registered as the multicore parallel backend to the 'foreach' package. If NULL, it will use a half of cores available in a user's computer. This option only works when parallel computation is enabled
 #' @param verbose logical to indicate whether the messages will be displayed in the screen. By default, it sets to TRUE for display
 #' @param RData.ontology.customised a file name for RData-formatted file containing an object of S4 class 'Onto' (i.g. ontology). By default, it is NULL. It is only needed when the user wants to perform customised analysis using their own ontology. See \code{\link{dcBuildOnto}} for how to creat this object
-#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "http://supfam.org/dcGOR/data" or "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first)
+#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR" and "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first). Here is the UNIX command for downloading all RData files (preserving the directory structure): \eqn{wget -r -l2 -A "*.RData" -np -nH --cut-dirs=0 "http://dcgor.r-forge.r-project.org/data"}
 #' @return 
 #' a data frame containing three columns: 1st column 'Feature_id' for features, 2nd 'Term_id' for terms, and 3rd 'Score' for the hypergeometric score indicative of strength of associations beteen features and terms
 #' @note
@@ -43,7 +43,7 @@
 #' res[1:5,]
 #' }
 
-dcAlgo <- function(anno.file, architecture.file, output.file=NULL, ontology=c(NA,"GOBP","GOMF","GOCC","DO","HPPA","HPMI","HPON","MP","EC","KW","UP"), feature.mode=c("supra","individual","comb"), min.overlap=3, fdr.cutoff=1e-3, hscore.type=c("zscore","fdr"), parallel=TRUE, multicores=NULL, verbose=T, RData.ontology.customised=NULL, RData.location="http://dcgor.r-forge.r-project.org/data")
+dcAlgo <- function(anno.file, architecture.file, output.file=NULL, ontology=c(NA,"GOBP","GOMF","GOCC","DO","HPPA","HPMI","HPON","MP","EC","KW","UP"), feature.mode=c("supra","individual","comb"), min.overlap=3, fdr.cutoff=1e-3, hscore.type=c("zscore","fdr"), parallel=TRUE, multicores=NULL, verbose=T, RData.ontology.customised=NULL, RData.location="https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR")
 {
 
     startT <- Sys.time()

R/dcAlgoPredict.r

@@ -13,7 +13,7 @@
 #' @param multicores an integer to specify how many cores will be registered as the multicore parallel backend to the 'foreach' package. If NULL, it will use a half of cores available in a user's computer. This option only works when parallel computation is enabled
 #' @param verbose logical to indicate whether the messages will be displayed in the screen. By default, it sets to TRUE for display
 #' @param RData.HIS.customised a file name for RData-formatted file containing an object of S3 class 'HIS'. By default, it is NULL. It is only needed when the user wants to perform customised analysis. See \code{\link{dcAlgoPropagate}} on how this object is created
-#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "http://supfam.org/dcGOR/data" or "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first)
+#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR" and "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first). Here is the UNIX command for downloading all RData files (preserving the directory structure): \eqn{wget -r -l2 -A "*.RData" -np -nH --cut-dirs=0 "http://dcgor.r-forge.r-project.org/data"}
 #' @return 
 #' a named list of architectures, each containing predictive scores
 #' @note none
@@ -47,7 +47,7 @@
 #' dnet::visDAG(g=subg, data=data, node.info="term_id")
 #' }
 
-dcAlgoPredict <- function(data, RData.HIS=c(NA,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="http://dcgor.r-forge.r-project.org/data")
+dcAlgoPredict <- function(data, RData.HIS=c(NA,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR")
 {
 
     startT <- Sys.time()

R/dcAlgoPredictGenome.r

@@ -14,7 +14,7 @@
 #' @param multicores an integer to specify how many cores will be registered as the multicore parallel backend to the 'foreach' package. If NULL, it will use a half of cores available in a user's computer. This option only works when parallel computation is enabled
 #' @param verbose logical to indicate whether the messages will be displayed in the screen. By default, it sets to TRUE for display
 #' @param RData.HIS.customised a file name for RData-formatted file containing an object of S3 class 'HIS'. By default, it is NULL. It is only needed when the user wants to perform customised analysis. See \code{\link{dcAlgoPropagate}} on how this object is created
-#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "http://supfam.org/dcGOR/data" or "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first)
+#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR" and "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first). Here is the UNIX command for downloading all RData files (preserving the directory structure): \eqn{wget -r -l2 -A "*.RData" -np -nH --cut-dirs=0 "http://dcgor.r-forge.r-project.org/data"}
 #' @return 
 #' a matrix of terms X genomes, containing the predicted scores (per genome) as a whole
 #' @note
@@ -43,7 +43,7 @@
 #' output[1:10,]
 #' }
 
-dcAlgoPredictGenome <- function(input.file, RData.HIS=c(NULL,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), weight.method=c("none","copynum","ic","both"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="http://dcgor.r-forge.r-project.org/data")
+dcAlgoPredictGenome <- function(input.file, RData.HIS=c(NULL,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), weight.method=c("none","copynum","ic","both"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR")
 {
 
     startT <- Sys.time()

R/dcAlgoPredictMain.r

@@ -14,7 +14,7 @@
 #' @param multicores an integer to specify how many cores will be registered as the multicore parallel backend to the 'foreach' package. If NULL, it will use a half of cores available in a user's computer. This option only works when parallel computation is enabled
 #' @param verbose logical to indicate whether the messages will be displayed in the screen. By default, it sets to TRUE for display
 #' @param RData.HIS.customised a file name for RData-formatted file containing an object of S3 class 'HIS'. By default, it is NULL. It is only needed when the user wants to perform customised analysis. See \code{\link{dcAlgoPropagate}} on how this object is created
-#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "http://supfam.org/dcGOR/data" or "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first)
+#' @param RData.location the characters to tell the location of built-in RData files. By default, it remotely locates at "https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR" and "http://dcgor.r-forge.r-project.org/data". For the user equipped with fast internet connection, this option can be just left as default. But it is always advisable to download these files locally. Especially when the user needs to run this function many times, there is no need to ask the function to remotely download every time (also it will unnecessarily increase the runtime). For examples, these files (as a whole or part of them) can be first downloaded into your current working directory, and then set this option as: \eqn{RData.location="."}. If RData to load is already part of package itself, this parameter can be ignored (since this function will try to load it via function \code{data} first). Here is the UNIX command for downloading all RData files (preserving the directory structure): \eqn{wget -r -l2 -A "*.RData" -np -nH --cut-dirs=0 "http://dcgor.r-forge.r-project.org/data"}
 #' @return 
 #' a data frame containing three columns: 1st column the same as the input file (e.g. 'SeqID'), 2nd for 'Term' (predicted ontology terms), 3rd for 'Score' (along with predicted scores)
 #' @note
@@ -41,7 +41,7 @@
 #' output[1:5,]
 #' }
 
-dcAlgoPredictMain <- function(input.file, output.file=NULL, RData.HIS=c(NA,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="http://dcgor.r-forge.r-project.org/data")
+dcAlgoPredictMain <- function(input.file, output.file=NULL, RData.HIS=c(NA,"Feature2GOBP.sf","Feature2GOMF.sf","Feature2GOCC.sf","Feature2HPPA.sf","Feature2GOBP.pfam","Feature2GOMF.pfam","Feature2GOCC.pfam","Feature2HPPA.pfam","Feature2GOBP.interpro","Feature2GOMF.interpro","Feature2GOCC.interpro","Feature2HPPA.interpro"), merge.method=c("sum","max","sequential"), scale.method=c("log","linear","none"), feature.mode=c("supra","individual","comb"), slim.level=NULL, max.num=NULL, parallel=TRUE, multicores=NULL, verbose=T, RData.HIS.customised=NULL, RData.location="https://github.com/hfang-bristol/RDataCentre/blob/master/dcGOR")
 {
 
     startT <- Sys.time()