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Added @export decorator for Github actions
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@soelmicheletti
soelmicheletti authored Nov 12, 2024
1 parent 1b3619a commit d8f9d9b
Showing 1 changed file with 39 additions and 1 deletion.
40 changes: 39 additions & 1 deletion R/NetworkDataCompanion.R
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Returns a named list with rds_sample_info corresponding to meta information about the samples (columns)
## and rds_gene_info corresponding to meta information about genes (rows)
## 20220913: man page done
#' @export
extractSampleAndGeneInfo = function(expression_rds_obj){
return(list(rds_sample_info=as.data.frame(colData(expression_rds_obj)),
rds_gene_info=as.data.frame(rowRanges(expression_rds_obj))))
Expand All @@ -26,6 +27,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## exp1[,is_inter1] --- this will remove samples that are not in exp2
## exp2[,idcs1[is_inter1]] --- this will remove samples that are not in exp1 and reorder to match exp1
## 20220920 man page done
#' @export
mapBarcodeToBarcode = function(bc1, bc2){
if(class(bc1) != "character" | class(bc2) != "character"){
stop("Error: barcodes need to be vectors of strings")
Expand All @@ -39,6 +41,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## returns a list of the two argument data frames, intersected, and the second frame ordered to match the first
## NOTE: Ordering is done based on columns, which are expected to be named by TCGA barcodes
## 20220920 man page done
#' @export
filterBarcodesIntersection = function(exp1, exp2){
if(!("data.frame" %in% class(exp1) | "matrix" %in% class(exp1)) ){
stop("Error: argument 1 needs to be data.frame or matrix")
Expand All @@ -56,6 +59,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## TPM data.frame (useful for TPM based filtering, see filterGenesByNormExpression)
## and the actual logTPM which corresponds to log(TPM + 1)
## 20220920 man page done
#' @export
logTPMNormalization = function(expression_rds_obj){
if(class(expression_rds_obj) != "RangedSummarizedExperiment"){
stop("Error: expression matrices need to be an RSE object")
Expand All @@ -72,6 +76,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Returns a named list with the count data.frame (useful for duplicate filtering based on sequencing depth, see filterDuplicatesSeqDepth)
## CPM data.frame (useful for CPM based filtering, see filterGenesByCPM)
## and the actual logCPM which corresponds to log(CPM + 1)
#' @export
logCPMNormalization = function(exp_count_mat){
if(sum(class(exp_count_mat) %in% c("data.frame", "matrix")) == 0){
stop("Error: expression must be a matrix")
Expand All @@ -90,33 +95,39 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
#### more methods go here

# maybe have this presaved in class
#' @export
extractSampleOnly = function(TCGA_barcodes){
return(sapply(TCGA_barcodes, substr, 1, 12))
},

#' @export
extractSampleAndType = function(TCGA_barcodes){
return(sapply(TCGA_barcodes, substr, 1, 15))
},

#' @export
extractSampleAndTypeAndVial = function(TCGA_barcodes){
return(sapply(TCGA_barcodes, substr, 1, 16))
},


#' @export
extractSampleType = function(TCGA_barcodes){
return(sapply(TCGA_barcodes, substr, 14, 15))
},

#' @export
extractVialOnly = function(TCGA_barcodes){
return(sapply(TCGA_barcodes, substr, 16, 16))
},

#' @export
findDuplicates = function(TCGA_barcodes){
dupPos = duplicated(extractSampleAndTypeAndVial(TCGA_barcodes))
return(TCGA_barcodes[dupPos])
},

# UUIDs is a character vector
#' @export
mapNewUUIDVersion = function(UUIDs)
{
updateUUIDVersion = function(x){
Expand All @@ -131,6 +142,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

# UUIDs is a character vector (can be of length 1)
#' @export
mapUUIDtoTCGA = function(UUIDs){
if(class(UUIDs) != "character"){
stop("Error: Expected UUID argument to be a character vector")
Expand Down Expand Up @@ -168,6 +180,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
# long form: returns one row per gene, so if a probe maps
# to the TSS of two different genes, each of those gets a row
# default if probelist is NULL is to map all the probes in the manifest
#' @export
mapProbesToGenes = function(probelist = NULL,
rangeUp = 200,
rangeDown = 0,
Expand Down Expand Up @@ -276,6 +289,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
# Function to map to probes to a gene-level measurement
# probe_gene_map is in the format output from the mapProbesToGenes function
# not all genesOfInterest need to be in probe_gene_map, but if none are, then this is meaningless
#' @export
probeToMeanPromoterMethylation = function(methylation_betas,
probe_gene_map,
genesOfInterest = NULL){
Expand Down Expand Up @@ -321,12 +335,14 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
# Input to convertBetaToM is a vector of methylation betas
# User should use this function with `apply` to convert a matrix
# 20220920 man page done
#' @export
convertBetaToM = function(methylation_betas){
M = log2(methylation_betas/(1-methylation_betas))
return(M)
},

## Run EPISCORE to estimate cell counts
#' @export
estimateCellCountsEpiSCORE = function(methylation_betas, tissue, array = "450k"){
tissue_options = c("Bladder",
"Brain",
Expand Down Expand Up @@ -430,6 +446,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## Extract AHRR methylation at probe site cg05575921 as a proxy for smoking status
#' @export
extractAHRRMethylation = function(methylation_betas)
{
ahrr = methylation_betas %>%
Expand All @@ -443,6 +460,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Filter out all duplicates based on sequencing depth
## Returns indices about which samples to KEEP
## 20220920 man page done
#' @export
filterDuplicatesSeqDepth = function(expression_count_matrix){
sample_barcodes <- extractSampleAndType(colnames(expression_count_matrix))
seq_depth <- colSums(expression_count_matrix)
Expand All @@ -466,6 +484,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Filter out all duplicates based on sequencing depth, take random one if no info on seq depth for all vials
## Returns indices in given tcga barcodes to KEEP
## 20220920 man page done
#' @export
filterDuplicatesSeqDepthOther = function(expression_count_matrix, tcga_barcodes){
sample_vials_ge <- extractSampleAndTypeAndVial(colnames(expression_count_matrix))
seq_depth <- colSums(expression_count_matrix)
Expand Down Expand Up @@ -504,6 +523,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Filter samples indicated by *TCGA_barcodes* based on the method *method* and threshold *threshold*
## Returns a list of indices indicating which samples should be kept
## 20220920 Man page done
#' @export
filterPurity = function(TCGA_barcodes, method="ESTIMATE", threshold=.6){
if(class(TCGA_barcodes) != "character"){
stop("Error: Expected TCGA_barcodes argument to be vector of strings")
Expand All @@ -524,6 +544,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

# return tissue type given an input barcode
#' @export
getTissueType = function(TCGA_barcode)
{
this_sample = substr(str_split(TCGA_barcode,"-",simplify=T)[1,4],1,2)
Expand All @@ -544,6 +565,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(sample_type_mapping)
},
## Filtering samples in an rds with particular sample types (e.g., "Primary Tumor", "Solid Tissue Normal", "Primary Blood Derived Cancer - Peripheral Blood")
#' @export
filterSampleType = function(TCGA_barcodes, types_of_samples){
if(class(TCGA_barcodes) != "character"){
stop("Error: TCGA_barcodes argument needs to be a character vector")
Expand All @@ -568,6 +590,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## Filtering all tumor samples (e.g. barcode sample types {01,..09})
#' @export
filterTumorSamples = function(TCGA_barcodes){
if(class(TCGA_barcodes) != "character"){
stop("Error: TCGA_barcodes argument needs to be a character vector")
Expand All @@ -582,6 +605,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## Filtering all normal samples (e.g. barcode sample types {10,..19})
#' @export
filterNormalSamples = function(TCGA_barcodes){
if(class(TCGA_barcodes) != "character"){
stop("Error: TCGA_barcodes argument needs to be a character vector")
Expand All @@ -596,6 +620,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## Filtering all control samples (e.g. barcode sample types {20,..29})
#' @export
filterControlSamples = function(TCGA_barcodes){
if(class(TCGA_barcodes) != "character"){
stop("Error: TCGA_barcodes argument needs to be a character vector")
Expand All @@ -612,6 +637,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",


## Filter out protein coding genes based on rds info
#' @export
filterGenesProteins = function(rds_gene_info){
if(class(rds_gene_info) != "data.frame"){
stop("Error: gene info argument should be a data.frame. Best \
Expand All @@ -624,6 +650,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
## Filter all genes which have at least *norm_threshold* scores (of normalized gene expression) in at least *sample_fraction* of samples
## expression_matrix should be TPM or CPM values (NOT log scaled)
## sample_fraction should be in [0,1]
#' @export
filterGenesByNormExpression = function(expression_matrix, norm_threshold, sample_fraction){
if(sum(class(expression_matrix) %in% c("data.frame","matrix")) == 0) {
stop("Error: expression_matrix argument should be a data.frame")
Expand All @@ -640,6 +667,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## 20220921 man page done
#' @export
filterChromosome = function(rds_gene_info, chroms){
if(class(rds_gene_info) != "data.frame"){
stop("Error: gene info argument should be a data.frame. Best \
Expand All @@ -655,6 +683,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
##gets gene information from gencode given a list of genes names or ids from the gene mapping variable
##automatically infers whether ensmbl ID or name or entrez
##automatically infers whether version (i.e., the dot) exists in ensemble ID
#' @export
getGeneInfo = function(gene_names_or_ids_or_entrezs){
is_id <- any(grepl("ENSG", gene_names_or_ids_or_entrezs, fixed=TRUE))
is_entrez <- any(grepl("^\\d+$", gene_names_or_ids_or_entrezs))
Expand Down Expand Up @@ -682,6 +711,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## the version corresponds to whether we want the . and number after from gene ids
#' @export
geneEntrezToENSG = function(gene_entrezs, version = FALSE){
if(!("gene_entrez" %in% colnames(gene_mapping)))
{
Expand All @@ -697,6 +727,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(to_return)
},

#' @export
geneENSGToName = function(gene_ids){
to_return <- getGeneInfo(gene_ids)
if(anyNA(to_return$gene_name)){
Expand All @@ -705,6 +736,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(to_return[c('gene_id_no_ver','gene_name')])
},

#' @export
geneENSGToEntrez = function(gene_ids){
if(!("gene_entrez" %in% colnames(gene_mapping)))
{
Expand All @@ -717,6 +749,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(to_return[c('gene_id_no_ver','gene_entrez')])
},

#' @export
geneNameToEntrez = function(gene_names){
if(!("gene_entrez" %in% colnames(gene_mapping)))
{
Expand All @@ -731,6 +764,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(to_return)
},

#' @export
geneEntrezToName = function(gene_entrezs){
if(!("gene_entrez" %in% colnames(gene_mapping)))
{
Expand All @@ -746,6 +780,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
},

## the version corresponds to whether we want the . and number after from gene ids
#' @export
geneNameToENSG = function(gene_names, version = FALSE){
to_return <- getGeneInfo(gene_names)
if(version == TRUE){
Expand All @@ -757,6 +792,7 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(to_return)
},

#' @export
getGeneIdcs = function(gene_names, rds_gene_info){
if(class(rds_gene_info) != "data.frame"){
stop("Error: gene info argument should be a data.frame. Best \
Expand All @@ -769,13 +805,15 @@ NetworkDataCompanion=setRefClass("NetworkDataCompanion",
return(match(gene_names, rds_gene_info$gene_name))
},

#' @export
getStage = function(TCGA_barcodes){
sample_names <- extractSampleOnly(TCGA_barcodes)
stage_names <- clinical_patient_data$bcr_patient_barcode
stages <- clinical_patient_data$ajcc_pathologic_tumor_stage[match(sample_names, stage_names)]
return(stages)
},

#' @export
getSex = function(TCGA_barcodes){
sample_names <- extractSampleOnly(TCGA_barcodes)
sex_names <- clinical_patient_data$bcr_patient_barcode
Expand Down

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