Mercurial > repos > iuc > raceid_filtnormconf
comparison scripts/cluster.R @ 3:d55e29ac02e3 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/raceid3 commit d94b3b8a4c7cf8c604279eb1eea24d32b3868922
author | iuc |
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date | Mon, 15 Apr 2019 17:55:17 -0400 |
parents | 56a093c2a3f9 |
children | 5d5b14dbd092 |
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2:56a093c2a3f9 | 3:d55e29ac02e3 |
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1 #!/usr/bin/env R | 1 #!/usr/bin/env R |
2 VERSION = "0.3" | 2 VERSION = "0.4" |
3 | 3 |
4 args = commandArgs(trailingOnly = T) | 4 args = commandArgs(trailingOnly = T) |
5 | 5 |
6 if (length(args) != 1){ | 6 if (length(args) != 1){ |
7 message(paste("VERSION:", VERSION)) | 7 message(paste("VERSION:", VERSION)) |
25 ## Get histogram metrics for library size and number of features | 25 ## Get histogram metrics for library size and number of features |
26 raw.lib <- log10(colSums(as.matrix(sc@expdata))) | 26 raw.lib <- log10(colSums(as.matrix(sc@expdata))) |
27 raw.feat <- log10(colSums(as.matrix(sc@expdata)>0)) | 27 raw.feat <- log10(colSums(as.matrix(sc@expdata)>0)) |
28 filt.lib <- log10(colSums(getfdata(sc))) | 28 filt.lib <- log10(colSums(getfdata(sc))) |
29 filt.feat <- log10(colSums(getfdata(sc)>0)) | 29 filt.feat <- log10(colSums(getfdata(sc)>0)) |
30 | |
31 if (filt.geqone){ | |
32 filt.feat <- log10(colSums(getfdata(sc)>=1)) | |
33 } | |
30 | 34 |
31 br <- 50 | 35 br <- 50 |
32 ## Determine limits on plots based on the unfiltered data | 36 ## Determine limits on plots based on the unfiltered data |
33 ## (doesn't work, R rejects limits and norm data is too different to compare to exp data | 37 ## (doesn't work, R rejects limits and norm data is too different to compare to exp data |
34 ## so let them keep their own ranges) | 38 ## so let them keep their own ranges) |
122 dg.goi.table <- head(dg.goi, genelist.tablelim) | 126 dg.goi.table <- head(dg.goi, genelist.tablelim) |
123 df <<- rbind(df, cbind(n, dg.goi.table)) | 127 df <<- rbind(df, cbind(n, dg.goi.table)) |
124 | 128 |
125 goi <- head(rownames(dg.goi.table), genelist.plotlim) | 129 goi <- head(rownames(dg.goi.table), genelist.plotlim) |
126 print(plotmarkergenes(sc, goi)) | 130 print(plotmarkergenes(sc, goi)) |
127 print(do.call(mtext, c(paste(" Cluster ",n), test))) ## spacing is a hack | 131 buffer <- paste(rep("", 36), collapse=" ") |
132 print(do.call(mtext, c(paste(buffer, "Cluster ",n), test))) ## spacing is a hack | |
128 test$line=-1 | 133 test$line=-1 |
129 print(do.call(mtext, c(paste(" Sig. Genes"), test))) ## spacing is a hack | 134 print(do.call(mtext, c(paste(buffer, "Sig. Genes"), test))) ## spacing is a hack |
130 test$line=-2 | 135 test$line=-2 |
131 print(do.call(mtext, c(paste(" (fc > ", genelist.foldchange,")"), test))) ## spacing is a hack | 136 print(do.call(mtext, c(paste(buffer, "(fc > ", genelist.foldchange,")"), test))) ## spacing is a hack |
132 | 137 |
133 }) | 138 }) |
134 write.table(df, file=out.genelist, sep="\t", quote=F) | 139 write.table(df, file=out.genelist, sep="\t", quote=F) |
135 } | 140 } |
136 | 141 |
137 pdf(out.pdf) | 142 pdf(out.pdf) |
138 | 143 |
139 if (use.filtnormconf){ | 144 if (use.filtnormconf){ |
140 sc <- do.filter(sc) | 145 sc <- do.filter(sc) |
141 message(paste(" - Source:: genes:",nrow(sc@expdata),", cells:",ncol(sc@expdata))) | 146 message(paste(" - Source:: genes:",nrow(sc@expdata),", cells:",ncol(sc@expdata))) |
142 message(paste(" - Filter:: genes:",nrow(sc@ndata),", cells:",ncol(sc@ndata))) | 147 message(paste(" - Filter:: genes:",nrow(getfdata(sc)),", cells:",ncol(getfdata(sc)))) |
143 message(paste(" :: ", | 148 message(paste(" :: ", |
144 sprintf("%.1f", 100 * nrow(sc@ndata)/nrow(sc@expdata)), "% of genes remain,", | 149 sprintf("%.1f", 100 * nrow(getfdata(sc))/nrow(sc@expdata)), "% of genes remain,", |
145 sprintf("%.1f", 100 * ncol(sc@ndata)/ncol(sc@expdata)), "% of cells remain")) | 150 sprintf("%.1f", 100 * ncol(getfdata(sc))/ncol(sc@expdata)), "% of cells remain")) |
146 } | 151 } |
147 | 152 |
148 if (use.cluster){ | 153 if (use.cluster){ |
149 par(mfrow=c(2,2)) | 154 par(mfrow=c(2,2)) |
150 sc <- do.cluster(sc) | 155 sc <- do.cluster(sc) |