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improved performance on large datasets

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robocopAlpha 2020-07-29 12:13:12 +03:00
parent e20a2c05f3
commit 64d4567b20
1 changed files with 11 additions and 11 deletions
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22
unparalogMutations.R
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@ -28,7 +28,7 @@
unparalog <- function(DATA, paralog_separator = ";", annotation_separator = ",", GeneColName , AnnotationColName ){
# Installing missing dependencies
dependencies <- c("stringi", "progress")
dependencies <- c("stringi", "progress","data.table")
missing_packages <- dependencies[!(dependencies %in% installed.packages()[, "Package"])]
if(length(missing_packages)) install.packages(missing_packages)
@ -51,7 +51,7 @@ unparalog <- function(DATA, paralog_separator = ";", annotation_separator = ",",
rm(missing_packages,dependencies,check_paralog_sep,check_annotation_sep)
gc()
current.idx <- nrow(DATA)+1
current.idx <- 1 # nrow(DATA)+1
paralog.idx <- which(stringi::stri_detect_fixed(str = DATA$Gene.refGene,pattern = paralog_separator))
pb <- progress::progress_bar$new(total=length(paralog.idx),format = " [:bar] :current/:total (:percent)",); pb$tick(0)
@ -59,27 +59,27 @@ unparalog <- function(DATA, paralog_separator = ";", annotation_separator = ",",
message(stringi::stri_c("There are ",length(paralog.idx)," annotations with ", Number_of_paralogs," paralogs."))
# copying structure of original DATA
DATA.add <- DATA[1,]; DATA.add <- DATA.add[-1,]
DATA.new <- DATA[1,]; DATA.new <- DATA.new[-1,]
# Adding the empty rows to original table.
# These rows will be populated in the for loop
DATA.add <- dplyr::bind_rows(DATA.add,data.frame(matrix(nrow = (length(paralog.idx)+Number_of_paralogs), ncol = ncol(DATA),dimnames = list(c(),colnames(DATA))),stringsAsFactors = F))
DATA <- dplyr::bind_rows(DATA,DATA.add)
rm(DATA.add) ; gc()
# Creating empty table which will be populated in the for loop
DATA.new <- dplyr::bind_rows(DATA.new,data.frame(matrix(nrow = (length(paralog.idx)+Number_of_paralogs), ncol = ncol(DATA),dimnames = list(c(),colnames(DATA))),stringsAsFactors = F))
# Beginning isolation of the paralogs
for(i in paralog.idx){
Muts <- unlist(stringi::stri_split_fixed(DATA$AAChange.refGene[i],annotation_separator),use.names = F,recursive = F)
for (gene in unlist(stringi::stri_split_fixed(DATA$Gene.refGene[i],pattern = paralog_separator),use.names = F,recursive = F)){
DATA[current.idx,] <- DATA[i,]
DATA$Gene.refGene[current.idx] <- gene
DATA$AAChange.refGene[current.idx] <- paste0(Muts[grep(gene,Muts,fixed = T)],collapse=",")
DATA.new[current.idx,] <- DATA[i,]
DATA.new$Gene.refGene[current.idx] <- gene
DATA.new$AAChange.refGene[current.idx] <- paste0(Muts[grep(gene,Muts,fixed = T)],collapse=annotation_separator)
current.idx <- current.idx+1
}
pb$tick(1)
}
# removing the original rows with the paralogs as they are all unparalogged now
DATA <- DATA[-paralog.idx,]
DATA <- dplyr::bind_rows(DATA,DATA.new)
rm(DATA.new) ; gc()
rownames(DATA) <- as.character(seq(1,length(DATA[,1])))
return (DATA)
}