Mercurial > repos > iuc > raceid_clustering
diff scripts/trajectoryinspect.R @ 6:a4b734cd253b draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/raceid3 commit 53916f6803b93234f992f5fd4fad61d7013d82af"
author | iuc |
---|---|
date | Thu, 15 Apr 2021 18:58:21 +0000 |
parents | 4ea021bd7513 |
children | 0bff0ee0683a |
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--- a/scripts/trajectoryinspect.R Wed Jan 29 17:16:36 2020 -0500 +++ b/scripts/trajectoryinspect.R Thu Apr 15 18:58:21 2021 +0000 @@ -1,9 +1,9 @@ #!/usr/bin/env R -VERSION = "0.2" +VERSION <- "0.2" # nolint -args = commandArgs(trailingOnly = T) +args <- commandArgs(trailingOnly = T) -if (length(args) != 1){ +if (length(args) != 1) { message(paste("VERSION:", VERSION)) stop("Please provide the config file") } @@ -13,17 +13,17 @@ source(args[1]) test <- list() -test$side = 3 -test$line = 2.5 +test$side <- 3 +test$line <- 2.5 second <- test -second$cex = 0.5 -second$line = 2.5 +second$cex <- 0.5 +second$line <- 2.5 -do.trajectoryinspection.stemID <- function(ltr){ - makeBranchLink <- function(i,j,k){ - ingoing <- paste(sort(c(i,j)), collapse=".") - outgoing <- paste(sort(c(j,k)), collapse=".") - messed <- sort(c(ingoing,outgoing)) +do.trajectoryinspection.stemID <- function(ltr) { # nolint + makeBranchLink <- function(i, j, k) { # nolint + ingoing <- paste(sort(c(i, j)), collapse = ".") + outgoing <- paste(sort(c(j, k)), collapse = ".") + messed <- sort(c(ingoing, outgoing)) return(list(messed[[1]], messed[[2]])) } @@ -34,88 +34,99 @@ ) write.table( head(bra$diffgenes$z, trjsid.numdiffgenes), - file=out.diffgenes) + file = out.diffgenes) - par(mfrow = c(2,2), cex=0.5) - print(do.call(plotmap, c(bra$scl, final=FALSE, fr=FALSE))) + par(mfrow = c(3, 2), cex = 0.5) + print(do.call(plotmap, c(bra$scl, final = FALSE, fr = FALSE))) print(do.call(mtext, c("Initial Clusters (tSNE)", test))) - print(do.call(plotmap, c(bra$scl, final=TRUE, fr=FALSE))) + print(do.call(plotmap, c(bra$scl, final = TRUE, fr = FALSE))) print(do.call(mtext, c("Final Clusters (tSNE)", test))) - print(do.call(plotmap, c(bra$scl, final=FALSE, fr=TRUE))) + print(do.call(plotmap, c(bra$scl, final = FALSE, um = TRUE))) + print(do.call(mtext, c("Initial Clusters (UMAP)", test))) + print(do.call(plotmap, c(bra$scl, final = TRUE, um = TRUE))) + print(do.call(mtext, c("Final Clusters (UMAP)", test))) + print(do.call(plotmap, c(bra$scl, final = FALSE, fr = TRUE))) print(do.call(mtext, c("Initial Clusters (F-R)", test))) - print(do.call(plotmap, c(bra$scl, final=TRUE, fr=TRUE))) + print(do.call(plotmap, c(bra$scl, final = TRUE, fr = TRUE))) print(do.call(mtext, c("Final Clusters (F-R)", test))) } -do.trajectoryinspection.fateID <- function(ltr){ +do.trajectoryinspection.fateID <- function(ltr) { # nolint n <- do.call(cellsfromtree, c(ltr, trjfid.cellsfrom)) x <- getfdata(ltr@sc) - trjfid.filterset$x = x - trjfid.filterset$n = n$f + trjfid.filterset$x <- x + trjfid.filterset$n <- n$f fs <- do.call(filterset, c(trjfid.filterset)) - trjfid.getsom$x = fs + trjfid.getsom$x <- fs s1d <- do.call(getsom, c(trjfid.getsom)) - trjfid.procsom$s1d = s1d + trjfid.procsom$s1d <- s1d ps <- do.call(procsom, c(trjfid.procsom)) y <- ltr@sc@cpart[n$f] fcol <- ltr@sc@fcol - trjfid.plotheat$xpart = y - trjfid.plotheat$xcol = fcol + trjfid.plotheat$xpart <- y + trjfid.plotheat$xcol <- fcol + + test$side <- 3 + test$line <- 3 ##Plot average z-score for all modules derived from the SOM: - trjfid.plotheat$x = ps$nodes.z - trjfid.plotheat$ypart = unique(ps$nodes) + trjfid.plotheat$x <- ps$nodes.z + trjfid.plotheat$ypart <- unique(ps$nodes) print(do.call(plotheatmap, c(trjfid.plotheat))) - print(do.call(mtext, c("Average z-score for all modules derived from SOM", test))) + print(do.call(mtext, c("Average z-score for all modules derived from SOM", + test))) ##Plot z-score profile of each gene ordered by SOM modules: - trjfid.plotheat$x = ps$all.z - trjfid.plotheat$ypart = ps$nodes + trjfid.plotheat$x <- ps$all.z + trjfid.plotheat$ypart <- ps$nodes print(do.call(plotheatmap, c(trjfid.plotheat))) - print(do.call(mtext, c("z-score profile of each gene ordered by SOM modules", test))) + print(do.call(mtext, c(paste0("z-score profile of each gene", + "ordered by SOM modules"), test))) ##Plot normalized expression profile of each gene ordered by SOM modules: - trjfid.plotheat$x = ps$all.e - trjfid.plotheat$ypart = ps$nodes + trjfid.plotheat$x <- ps$all.e + trjfid.plotheat$ypart <- ps$nodes print(do.call(plotheatmap, c(trjfid.plotheat))) - print(do.call(mtext, c("Normalized expression profile of each gene ordered by SOM modules", test))) - ##Plot binarized expression profile of each gene (z-score < -1, -1 < z-score < 1, z-score > 1): - trjfid.plotheat$x = ps$all.b - trjfid.plotheat$ypart = ps$nodes + print(do.call(mtext, c(paste0("Normalized expression profile of each", + "gene ordered by SOM modules"), test))) + ##Plot binarized expression profile of each gene + ##(z-score < -1, -1 < z-score < 1, z-score > 1) + trjfid.plotheat$x <- ps$all.b + trjfid.plotheat$ypart <- ps$nodes print(do.call(plotheatmap, c(trjfid.plotheat))) print(do.call(mtext, c("Binarized expression profile of each gene", test))) ## This should be written out, and passed back into the tool ## to perform sominspect - return(list(fs=fs,ps=ps,y=y,fcol=fcol,nf=n$f)) + return(list(fs = fs, ps = ps, y = y, fcol = fcol, nf = n$f)) } -do.trajectoryinspection.fateID.sominspect <- function(domo){ +do.trajectoryinspection.fateID.sominspect <- function(domo) { # nolint g <- trjfidsomi.use.genes - if (class(g) == "numeric"){ + if (class(g) == "numeric") { g <- names(ps$nodes)[ps$nodes %in% g] } - typ = NULL - if (!is.null(trjfidsomi.use.types)){ - typ = sub(trjfidsomi.use.types,"", domo$nf) + typ <- NULL + if (!is.null(trjfidsomi.use.types)) { + typ <- sub(trjfidsomi.use.types, "", domo$nf) } - trjfidsomi$x = domo$fs - trjfidsomi$y = domo$y - trjfidsomi$g = g - trjfidsomi$n = domo$nf - trjfidsomi$col = domo$fcol - trjfidsomi$types = typ + trjfidsomi$x <- domo$fs + trjfidsomi$y <- domo$y + trjfidsomi$g <- g + trjfidsomi$n <- domo$nf + trjfidsomi$col <- domo$fcol + trjfidsomi$types <- typ ## The average pseudo-temporal expression profile of this group ## can be plotted by the function plotexpression: - par(mfrow = c(1,1)) - test$cex = 1 - second$line = 1.5 - if (trjfidsomi$name == "Title") trjfidsomi$name = "" + par(mfrow = c(1, 1)) + test$cex <- 1 + second$line <- 1.5 + if (trjfidsomi$name == "Title") trjfidsomi$name <- "" print(do.call(plotexpression, c(trjfidsomi))) - mess2 <- paste(c(trjfidsomi.use.genes), collapse=", ") + mess2 <- paste(c(trjfidsomi.use.genes), collapse = ", ") mess1 <- "Average pseudo-temporal expression profile" print(do.call(mtext, c(mess1, test))) print(do.call(mtext, c(mess2, second)))