Mercurial > repos > iuc > raceid_filtnormconf
changeset 1:01290f30211f draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/raceid3 commit 71e6b205841c83391ea8fc69e10eac03f212f4d6
| author | iuc |
|---|---|
| date | Thu, 28 Feb 2019 13:00:24 -0500 |
| parents | 8dc8ff057b0f |
| children | 56a093c2a3f9 |
| files | raceid_filtnormconf.xml scripts/cluster.R test-data/intestinal.filter.pdf test-data/intestinal_advanced.filter.pdf test-data/matrix.filter.pdf |
| diffstat | 5 files changed, 17 insertions(+), 10 deletions(-) [+] |
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--- a/raceid_filtnormconf.xml Thu Nov 22 04:44:44 2018 -0500 +++ b/raceid_filtnormconf.xml Thu Feb 28 13:00:24 2019 -0500 @@ -1,4 +1,4 @@ -<tool id="raceid_filtnormconf" name="Filtering, Normalisation, and Confounder Removal using RaceID" version="@VERSION_RACEID@.@VERSION_PACKAGE@.1" > +<tool id="raceid_filtnormconf" name="Filtering, Normalisation, and Confounder Removal using RaceID" version="@VERSION_RACEID@.@VERSION_PACKAGE@.2" > <description>generates a normalised and filtered count matrix of single-cell RNA data</description> <macros> <import>macros.xml</import>
--- a/scripts/cluster.R Thu Nov 22 04:44:44 2018 -0500 +++ b/scripts/cluster.R Thu Feb 28 13:00:24 2019 -0500 @@ -1,5 +1,5 @@ #!/usr/bin/env R -VERSION = "0.2" +VERSION = "0.3" args = commandArgs(trailingOnly = T) @@ -23,10 +23,10 @@ sc <- do.call(filterdata, c(sc, filt)) ## Get histogram metrics for library size and number of features - raw.lib <- log(colSums(as.matrix(sc@expdata))) - raw.feat <- log(rowSums(as.matrix(sc@expdata))) - filt.lib <- log(colSums(getfdata(sc))) - filt.feat <- log(rowSums(getfdata(sc))) + raw.lib <- log10(colSums(as.matrix(sc@expdata))) + raw.feat <- log10(rowSums(as.matrix(sc@expdata)>0)) + filt.lib <- log10(colSums(getfdata(sc))) + filt.feat <- log10(rowSums(getfdata(sc)>0)) br <- 50 ## Determine limits on plots based on the unfiltered data @@ -47,10 +47,17 @@ ## feat.x_lim <- c(0,betterrange(max(tmp.feat$breaks))) par(mfrow=c(2,2)) - print(hist(raw.lib, breaks=br, main="ExpData Log(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim) - print(hist(raw.feat, breaks=br, main="ExpData Log(NumFeat)")) #, xlim=feat.x_lim, ylim=feat.y_lim) - print(hist(filt.lib, breaks=br, main="FiltData Log(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim) - print(hist(filt.feat, breaks=br, main="FiltData Log(NumFeat)")) # , xlim=feat.x_lim, ylim=feat.y_lim) + print(hist(raw.lib, breaks=br, main="RawData Log10(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim) + print(hist(raw.feat, breaks=br, main="RawData Log10(NumFeat)")) #, xlim=feat.x_lim, ylim=feat.y_lim) + print(hist(filt.lib, breaks=br, main="FiltData Log10(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim) + tmp <- hist(filt.feat, breaks=br, main="FiltData Log10(NumFeat)") # , xlim=feat.x_lim, ylim=feat.y_lim) + print(tmp) # required, for extracting midpoint + unq <- unique(filt.feat) + if (length(unq) == 1){ + text(tmp$mids, table(filt.feat)[[1]] - 100, pos=1, paste(format(10^unq, scientific=T, digits=3), + " Features in all Cells", sep=""), cex=0.8) + } + if (filt.use.ccorrect){ par(mfrow=c(2,2))