R/filter_worker.R
In pmartR/pmartRmems:
#' Remove items that need to be filtered out
#'
#' This function removes
#'
#' @param omicsData an object of the class \code{pepData}, \code{proData}, \code{lipidData}, or \code{metabData}, usually created by \code{\link{as.pepData}}, \code{\link{as.proData}}, \code{\link{as.lipidData}}, or \code{\link{as.metabData}}, respectively.
#' @param filter_object a list created by the functions above
#' @return list
#' @author Kelly Stratton, Lisa Bramer
#'
MSomics_filter_worker <- function(filter_object, omicsData){
# pull column names from omicR_data attributes #
col_nms = attr(omicsData, "cnames")
samp_cname = col_nms$fdata_cname
edata_cname = col_nms$edata_cname
emeta_cname = col_nms$emeta_cname
# pull group_DF attribute #
group_DF = attr(omicsData, "group_DF")
#check if filter object contains remove arguments
if(!is.null(filter_object$edata_filt)||!is.null(filter_object$emeta_filt)||!is.null(filter_object$samples_filt)){
## check to see if e_meta is provided ##
# if not provided we only need to worry about e_data and f_data #
if(attr(omicsData, "meta_info") == FALSE){
## remove entries in edata ##
if(!is.null(filter_object$edata_filt) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_filt)
if(length(edat_ids) > 0){
# identify which peptides in e_data match filter list and remove #
temp.pep1 = temp.pep[-which(temp.pep[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.pep1 = temp.pep}
}else{ # no entries in edata need to be removed
temp.pep1 = omicsData$e_data
}
## remove samples ##
if(!is.null(filter_object$samples_filt) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_filt)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_filt)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[-which(temp.samp[,samp_cname] %in% filter_object$samples_filt),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and remove #
if(length(edat_ids2) > 0){
temp.pep2 = temp.pep1[, -which(names(temp.pep1) %in% filter_object$samples_filt)]
}else{temp.pep2 = temp.pep1}
}else{ # no entries in f_data need to be removed
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
temp.meta2 = NULL
}else{ # e_meta is present, so we need to work with it as well
## remove entries in edata ##
if(!is.null(filter_object$edata_filt) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_filt)
if(length(edat_ids) > 0){
# identify which peptides in e_data and e_meta match filter list and remove#
temp.pep1 = temp.pep[-which(temp.pep[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.pep1 = temp.pep}
temp.meta = omicsData$e_meta
# check that at least one of the peptides is present in e_meta #
emeta_ids = which(temp.meta[,edata_cname] %in% filter_object$edata_filt)
if(length(emeta_ids) > 0){
temp.meta1 = temp.meta[-which(temp.meta[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.meta1 = temp.meta}
}else{
temp.pep1 = omicsData$e_data
temp.meta1 = omicsData$e_meta
}
## remove samples ##
if(!is.null(filter_object$samples_filt) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_filt)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_filt)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[-which(temp.samp[,samp_cname] %in% filter_object$samples_filt),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and remove #
if(length(edat_ids2) > 0){
inds = which(names(temp.pep1) %in% filter_object$samples_filt)
temp.pep2 = temp.pep1[, -inds]
}else{temp.pep2 = temp.pep1}
}else{
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
## remove entries in emeta ##
if(!is.null(filter_object$emeta_filt) & !is.null(emeta_cname)){
# identify which proteins in data match filter list and remove from e_meta #
temp.meta = temp.meta1
# check that at least one of the proteins is in e_meta #
if(!is.null(ncol(temp.meta))){
emeta_ids2 = which(as.character(temp.meta[,emeta_cname]) %in% filter_object$emeta_filt)
}else{
emeta_ids2 = which(temp.meta %in% filter_object$emeta_filt)
}
if(length(emeta_ids2) > 0){
if(!is.null(ncol(temp.meta))){
temp.meta2 = temp.meta[-which(temp.meta[,emeta_cname] %in% filter_object$emeta_filt),]
}else{
temp.meta2 = temp.meta[-which(temp.meta %in% filter_object$emeta_filt)]
}
}else{temp.meta2 = temp.meta}
}else{
temp.meta2 = temp.meta1
}
# check for rogue entries in edata #
if(!is.null(ncol(temp.meta2))){
edat_ids2 = which(!(temp.pep2[,edata_cname] %in% temp.meta2[,edata_cname]))
}else{
edat_ids2 = which(!(temp.pep2[,edata_cname] %in% temp.meta2))
}
# filter out edata entries which no longer have mappings to emeta entries #
if(length(edat_ids2) > 0){
#temp.pep2 = temp.pep2[-which(!(temp.pep2[,edata_cname] %in% temp.meta2[,edata_cname])),]
temp.pep2 = temp.pep2[-edat_ids2,]
}
# filter out fdata entries which no longer have mappings to edata entries #
temp.fdata <- omicsData$f_data
fdat_ids <- which(!(temp.fdata[,samp_cname] %in% names(temp.pep2)[names(temp.pep2) != edata_cname]))
temp.samp2 <- temp.samp2[-fdat_ids,]
}
output <- list(temp.pep2 = temp.pep2, temp.samp2 = temp.samp2, temp.meta1 = temp.meta2, edata_cname = edata_cname, emeta_cname = emeta_cname, samp_cname = samp_cname)
}
#if filter object contains keep arguments
else{
## check to see if e_meta is provided ##
# if not provided we only need to worry about e_data and f_data #
if(attr(omicsData, "meta_info") == FALSE){
## keep entries in edata ##
if(!is.null(filter_object$edata_keep) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_keep)
if(length(edat_ids) > 0){
# identify which peptides in e_data match filter list and keep #
temp.pep1 = temp.pep[which(temp.pep[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.pep1 = temp.pep}
}else{ # no entries in edata need to be removed
temp.pep1 = omicsData$e_data
}
## keep samples ##
if(!is.null(filter_object$samples_keep) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_keep)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_keep)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[which(temp.samp[,samp_cname] %in% filter_object$samples_keep),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and keep #
if(length(edat_ids2) > 0){
edata_cname_id = which(names(temp.pep1) == edata_cname)
temp.pep2 = temp.pep1[,c(edata_cname_id,(which(names(temp.pep1) %in% filter_object$samples_keep)))]
}else{temp.pep2 = temp.pep1}
}else{ # no entries in f_data need to be removed
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
temp.meta2 = NULL
}else{ # e_meta is present, so we need to work with it as well
## keep entries in edata ##
if(!is.null(filter_object$edata_keep) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_keep)
if(length(edat_ids) > 0){
# identify which peptides in e_data and e_meta match filter list and keep#
temp.pep1 = temp.pep[which(temp.pep[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.pep1 = temp.pep}
temp.meta = omicsData$e_meta
# check that at least one of the peptides is present in e_meta #
emeta_ids = which(temp.meta[,edata_cname] %in% filter_object$edata_keep)
if(length(emeta_ids) > 0){
temp.meta1 = temp.meta[which(temp.meta[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.meta1 = temp.meta}
}else{
temp.pep1 = omicsData$e_data
temp.meta1 = omicsData$e_meta
}
## keep samples ##
if(!is.null(filter_object$samples_keep) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_keep)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_keep)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[which(temp.samp[,samp_cname] %in% filter_object$samples_keep),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and keep #
if(length(edat_ids2) > 0){
edata_cname_id = which(names(temp.pep1) == edata_cname)
inds = which(names(temp.pep1) %in% filter_object$samples_keep)
temp.pep2 = temp.pep1[,c(edata_cname_id,inds)]
}else{temp.pep2 = temp.pep1}
}else{
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
## keep entries in emeta ##
if(!is.null(filter_object$emeta_keep) & !is.null(emeta_cname)){
# identify which proteins in data match filter list and keep in e_meta #
temp.meta = temp.meta1
temp.meta_not_kept = omicsData$e_meta[-which(omicsData$e_meta$Mass_Tag_ID %in% temp.meta$Mass_Tag_ID),]
# check that at least one of the proteins is in e_meta (this is e_meta after e_data_keep has been applied) #
if(!is.null(ncol(temp.meta))){
emeta_ids2 = which(as.character(temp.meta[,emeta_cname]) %in% filter_object$emeta_keep)
}else{
emeta_ids2 = which(temp.meta %in% filter_object$emeta_keep)
}
# check that at least one of the proteins is in temp_meta_not_kept #
if(!is.null(ncol(temp.meta_not_kept))){
emeta_ids_not_kept = which(as.character(temp.meta_not_kept[,emeta_cname]) %in% filter_object$emeta_keep)
}else{
emeta_ids_not_kept = which(temp.meta_not_kept %in% filter_object$emeta_keep)
}
#if there are e_meta_keep (proteins) in the part of e_meta that we previously kept, then these proteins have already been kept
if(length(emeta_ids2) > 0){
if(!is.null(ncol(temp.meta))){
temp.meta2 = temp.meta
}else{
temp.meta2 = temp.meta
}
}else{temp.meta2 = temp.meta}
#if there are e_meta_keep(proteins) outside of e_meta that we previously kept we will keep these
if(length(emeta_ids_not_kept) > 0){
if(!is.null(ncol(temp.meta_not_kept))){
temp.meta3 = temp.meta_not_kept[which(temp.meta_not_kept[,emeta_cname] %in% filter_object$emeta_keep),]
temp.meta2 = rbind(temp.meta2,temp.meta3)
}else{
temp.meta3 = temp.meta_not_kept[which(temp.meta_not_kept %in% filter_object$emeta_keep)]
temp.meta2 = rbind(temp.meta2, temp.meta3)
}
}else{temp.meta2 = temp.meta}
}else{
temp.meta2 = temp.meta1
}
# check for entries in e_meta[,emeta_cname] that are not in e_data[,edata_cname]#
if(!is.null(ncol(temp.meta2))){
edat_ids2 = which(!temp.meta2[,edata_cname] %in% (temp.pep2[,edata_cname]))
}else{
edat_ids2 = which(!(temp.meta2 %in% temp.pep2[,edata_cname]))
}
# add edata entries which were present in emeta but not edata #
if(length(edat_ids2) > 0){
additional_peps<- temp.meta2$Mass_Tag_ID[edat_ids2]
edata_cname_id = which(names(temp.pep1) == edata_cname)
if(is.null(filter_object$samples_keep)){
inds = which(names(temp.pep1) %in% temp.samp2[,samp_cname])
}
else inds = which(names(temp.pep1) %in% filter_object$samples_keep)
temp.pep2 = rbind(temp.pep2, omicsData$e_data[which(omicsData$e_data$Mass_Tag_ID %in% additional_peps) ,c(edata_cname_id,inds)])
}
}
output <- list(temp.pep2 = temp.pep2, temp.samp2 = temp.samp2, temp.meta1 = temp.meta2, edata_cname = edata_cname, emeta_cname = emeta_cname, samp_cname = samp_cname)
}
# return the pieces needed to assemble a proData/pepData/lipidData/metabData object
return(output)
}
pmartR/pmartRmems documentation built on May 29, 2019, 4:52 p.m.
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#' Remove items that need to be filtered out
#'
#' This function removes
#'
#' @param omicsData an object of the class \code{pepData}, \code{proData}, \code{lipidData}, or \code{metabData}, usually created by \code{\link{as.pepData}}, \code{\link{as.proData}}, \code{\link{as.lipidData}}, or \code{\link{as.metabData}}, respectively.
#' @param filter_object a list created by the functions above
#' @return list
#' @author Kelly Stratton, Lisa Bramer
#'
MSomics_filter_worker <- function(filter_object, omicsData){
# pull column names from omicR_data attributes #
col_nms = attr(omicsData, "cnames")
samp_cname = col_nms$fdata_cname
edata_cname = col_nms$edata_cname
emeta_cname = col_nms$emeta_cname
# pull group_DF attribute #
group_DF = attr(omicsData, "group_DF")
#check if filter object contains remove arguments
if(!is.null(filter_object$edata_filt)||!is.null(filter_object$emeta_filt)||!is.null(filter_object$samples_filt)){
## check to see if e_meta is provided ##
# if not provided we only need to worry about e_data and f_data #
if(attr(omicsData, "meta_info") == FALSE){
## remove entries in edata ##
if(!is.null(filter_object$edata_filt) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_filt)
if(length(edat_ids) > 0){
# identify which peptides in e_data match filter list and remove #
temp.pep1 = temp.pep[-which(temp.pep[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.pep1 = temp.pep}
}else{ # no entries in edata need to be removed
temp.pep1 = omicsData$e_data
}
## remove samples ##
if(!is.null(filter_object$samples_filt) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_filt)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_filt)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[-which(temp.samp[,samp_cname] %in% filter_object$samples_filt),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and remove #
if(length(edat_ids2) > 0){
temp.pep2 = temp.pep1[, -which(names(temp.pep1) %in% filter_object$samples_filt)]
}else{temp.pep2 = temp.pep1}
}else{ # no entries in f_data need to be removed
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
temp.meta2 = NULL
}else{ # e_meta is present, so we need to work with it as well
## remove entries in edata ##
if(!is.null(filter_object$edata_filt) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_filt)
if(length(edat_ids) > 0){
# identify which peptides in e_data and e_meta match filter list and remove#
temp.pep1 = temp.pep[-which(temp.pep[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.pep1 = temp.pep}
temp.meta = omicsData$e_meta
# check that at least one of the peptides is present in e_meta #
emeta_ids = which(temp.meta[,edata_cname] %in% filter_object$edata_filt)
if(length(emeta_ids) > 0){
temp.meta1 = temp.meta[-which(temp.meta[,edata_cname] %in% filter_object$edata_filt),]
}else{temp.meta1 = temp.meta}
}else{
temp.pep1 = omicsData$e_data
temp.meta1 = omicsData$e_meta
}
## remove samples ##
if(!is.null(filter_object$samples_filt) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_filt)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_filt)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[-which(temp.samp[,samp_cname] %in% filter_object$samples_filt),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and remove #
if(length(edat_ids2) > 0){
inds = which(names(temp.pep1) %in% filter_object$samples_filt)
temp.pep2 = temp.pep1[, -inds]
}else{temp.pep2 = temp.pep1}
}else{
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
## remove entries in emeta ##
if(!is.null(filter_object$emeta_filt) & !is.null(emeta_cname)){
# identify which proteins in data match filter list and remove from e_meta #
temp.meta = temp.meta1
# check that at least one of the proteins is in e_meta #
if(!is.null(ncol(temp.meta))){
emeta_ids2 = which(as.character(temp.meta[,emeta_cname]) %in% filter_object$emeta_filt)
}else{
emeta_ids2 = which(temp.meta %in% filter_object$emeta_filt)
}
if(length(emeta_ids2) > 0){
if(!is.null(ncol(temp.meta))){
temp.meta2 = temp.meta[-which(temp.meta[,emeta_cname] %in% filter_object$emeta_filt),]
}else{
temp.meta2 = temp.meta[-which(temp.meta %in% filter_object$emeta_filt)]
}
}else{temp.meta2 = temp.meta}
}else{
temp.meta2 = temp.meta1
}
# check for rogue entries in edata #
if(!is.null(ncol(temp.meta2))){
edat_ids2 = which(!(temp.pep2[,edata_cname] %in% temp.meta2[,edata_cname]))
}else{
edat_ids2 = which(!(temp.pep2[,edata_cname] %in% temp.meta2))
}
# filter out edata entries which no longer have mappings to emeta entries #
if(length(edat_ids2) > 0){
#temp.pep2 = temp.pep2[-which(!(temp.pep2[,edata_cname] %in% temp.meta2[,edata_cname])),]
temp.pep2 = temp.pep2[-edat_ids2,]
}
# filter out fdata entries which no longer have mappings to edata entries #
temp.fdata <- omicsData$f_data
fdat_ids <- which(!(temp.fdata[,samp_cname] %in% names(temp.pep2)[names(temp.pep2) != edata_cname]))
temp.samp2 <- temp.samp2[-fdat_ids,]
}
output <- list(temp.pep2 = temp.pep2, temp.samp2 = temp.samp2, temp.meta1 = temp.meta2, edata_cname = edata_cname, emeta_cname = emeta_cname, samp_cname = samp_cname)
}
#if filter object contains keep arguments
else{
## check to see if e_meta is provided ##
# if not provided we only need to worry about e_data and f_data #
if(attr(omicsData, "meta_info") == FALSE){
## keep entries in edata ##
if(!is.null(filter_object$edata_keep) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_keep)
if(length(edat_ids) > 0){
# identify which peptides in e_data match filter list and keep #
temp.pep1 = temp.pep[which(temp.pep[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.pep1 = temp.pep}
}else{ # no entries in edata need to be removed
temp.pep1 = omicsData$e_data
}
## keep samples ##
if(!is.null(filter_object$samples_keep) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_keep)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_keep)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[which(temp.samp[,samp_cname] %in% filter_object$samples_keep),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and keep #
if(length(edat_ids2) > 0){
edata_cname_id = which(names(temp.pep1) == edata_cname)
temp.pep2 = temp.pep1[,c(edata_cname_id,(which(names(temp.pep1) %in% filter_object$samples_keep)))]
}else{temp.pep2 = temp.pep1}
}else{ # no entries in f_data need to be removed
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
temp.meta2 = NULL
}else{ # e_meta is present, so we need to work with it as well
## keep entries in edata ##
if(!is.null(filter_object$edata_keep) & !is.null(edata_cname)){
temp.pep = omicsData$e_data
# have to check that at least one of the items is present in the data #
edat_ids = which(temp.pep[,edata_cname] %in% filter_object$edata_keep)
if(length(edat_ids) > 0){
# identify which peptides in e_data and e_meta match filter list and keep#
temp.pep1 = temp.pep[which(temp.pep[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.pep1 = temp.pep}
temp.meta = omicsData$e_meta
# check that at least one of the peptides is present in e_meta #
emeta_ids = which(temp.meta[,edata_cname] %in% filter_object$edata_keep)
if(length(emeta_ids) > 0){
temp.meta1 = temp.meta[which(temp.meta[,edata_cname] %in% filter_object$edata_keep),]
}else{temp.meta1 = temp.meta}
}else{
temp.pep1 = omicsData$e_data
temp.meta1 = omicsData$e_meta
}
## keep samples ##
if(!is.null(filter_object$samples_keep) & !is.null(samp_cname)){
# identify which samples in f_data match filter list #
temp.samp = omicsData$f_data
# check that at least one sample is in f_data and e_data #
fdat_ids = which(temp.samp[,samp_cname] %in% filter_object$samples_keep)
edat_ids2 = which(names(temp.pep1) %in% filter_object$samples_keep)
if(length(fdat_ids) > 0){
temp.samp2 = temp.samp[which(temp.samp[,samp_cname] %in% filter_object$samples_keep),]
}else{temp.samp2 = temp.samp}
# identify which samples in e_data match filter list and keep #
if(length(edat_ids2) > 0){
edata_cname_id = which(names(temp.pep1) == edata_cname)
inds = which(names(temp.pep1) %in% filter_object$samples_keep)
temp.pep2 = temp.pep1[,c(edata_cname_id,inds)]
}else{temp.pep2 = temp.pep1}
}else{
temp.samp2 = omicsData$f_data
temp.pep2 = temp.pep1
}
## keep entries in emeta ##
if(!is.null(filter_object$emeta_keep) & !is.null(emeta_cname)){
# identify which proteins in data match filter list and keep in e_meta #
temp.meta = temp.meta1
temp.meta_not_kept = omicsData$e_meta[-which(omicsData$e_meta$Mass_Tag_ID %in% temp.meta$Mass_Tag_ID),]
# check that at least one of the proteins is in e_meta (this is e_meta after e_data_keep has been applied) #
if(!is.null(ncol(temp.meta))){
emeta_ids2 = which(as.character(temp.meta[,emeta_cname]) %in% filter_object$emeta_keep)
}else{
emeta_ids2 = which(temp.meta %in% filter_object$emeta_keep)
}
# check that at least one of the proteins is in temp_meta_not_kept #
if(!is.null(ncol(temp.meta_not_kept))){
emeta_ids_not_kept = which(as.character(temp.meta_not_kept[,emeta_cname]) %in% filter_object$emeta_keep)
}else{
emeta_ids_not_kept = which(temp.meta_not_kept %in% filter_object$emeta_keep)
}
#if there are e_meta_keep (proteins) in the part of e_meta that we previously kept, then these proteins have already been kept
if(length(emeta_ids2) > 0){
if(!is.null(ncol(temp.meta))){
temp.meta2 = temp.meta
}else{
temp.meta2 = temp.meta
}
}else{temp.meta2 = temp.meta}
#if there are e_meta_keep(proteins) outside of e_meta that we previously kept we will keep these
if(length(emeta_ids_not_kept) > 0){
if(!is.null(ncol(temp.meta_not_kept))){
temp.meta3 = temp.meta_not_kept[which(temp.meta_not_kept[,emeta_cname] %in% filter_object$emeta_keep),]
temp.meta2 = rbind(temp.meta2,temp.meta3)
}else{
temp.meta3 = temp.meta_not_kept[which(temp.meta_not_kept %in% filter_object$emeta_keep)]
temp.meta2 = rbind(temp.meta2, temp.meta3)
}
}else{temp.meta2 = temp.meta}
}else{
temp.meta2 = temp.meta1
}
# check for entries in e_meta[,emeta_cname] that are not in e_data[,edata_cname]#
if(!is.null(ncol(temp.meta2))){
edat_ids2 = which(!temp.meta2[,edata_cname] %in% (temp.pep2[,edata_cname]))
}else{
edat_ids2 = which(!(temp.meta2 %in% temp.pep2[,edata_cname]))
}
# add edata entries which were present in emeta but not edata #
if(length(edat_ids2) > 0){
additional_peps<- temp.meta2$Mass_Tag_ID[edat_ids2]
edata_cname_id = which(names(temp.pep1) == edata_cname)
if(is.null(filter_object$samples_keep)){
inds = which(names(temp.pep1) %in% temp.samp2[,samp_cname])
}
else inds = which(names(temp.pep1) %in% filter_object$samples_keep)
temp.pep2 = rbind(temp.pep2, omicsData$e_data[which(omicsData$e_data$Mass_Tag_ID %in% additional_peps) ,c(edata_cname_id,inds)])
}
}
output <- list(temp.pep2 = temp.pep2, temp.samp2 = temp.samp2, temp.meta1 = temp.meta2, edata_cname = edata_cname, emeta_cname = emeta_cname, samp_cname = samp_cname)
}
# return the pieces needed to assemble a proData/pepData/lipidData/metabData object
return(output)
}
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