Mercurial > repos > artbio > small_rna_maps

comparison small_rna_maps.r @ 30:183bf49fe77c draft

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"planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d280e9be7cf96f4938a73ccf5985533109f3328f"
author artbio
date Sat, 05 Oct 2019 18:25:19 -0400
parents fe1a9cfaf5c3
children f2e7ad3058e8
comparison
equal deleted inserted replaced
29:8b5695592784 30:183bf49fe77c
24 24
25 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list) 25 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
26 args = parse_args(parser) 26 args = parse_args(parser)
27 27
28 # data frames implementation 28 # data frames implementation
29
29 ## first table 30 ## first table
30 Table = read.delim(args$first_dataframe, header=T, row.names=NULL) 31 Table = read.delim(args$first_dataframe, header=T, row.names=NULL)
31 colnames(Table)[1] <- "Dataset" 32 colnames(Table)[1] <- "Dataset"
33 dropcol <- c("Strandness", "z.score") # not used by this Rscript and is dropped for backward compatibility
34 Table <- Table[,!(names(Table) %in% dropcol)]
32 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size") { 35 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size") {
33 Table <- within(Table, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1)) 36 Table <- within(Table, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1))
34 } 37 }
35 n_samples=length(unique(Table$Dataset)) 38 n_samples=length(unique(Table$Dataset))
36 samples = unique(Table$Dataset) 39 samples = unique(Table$Dataset)
40 norm_factors = rep(1, n_samples) 43 norm_factors = rep(1, n_samples)
41 } 44 }
42 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size" | args$first_plot_method == "Coverage") { 45 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size" | args$first_plot_method == "Coverage") {
43 i = 1 46 i = 1
44 for (sample in samples) { 47 for (sample in samples) {
48 # Warning
49 # Here the column is hard coded as the last column (dangerous)
50 # because its name changes with the method
45 Table[, length(Table)][Table$Dataset==sample] <- Table[, length(Table)][Table$Dataset==sample]*norm_factors[i] 51 Table[, length(Table)][Table$Dataset==sample] <- Table[, length(Table)][Table$Dataset==sample]*norm_factors[i]
46 i = i + 1 52 i = i + 1
47 } 53 }
48 } 54 }
49 genes=unique(Table$Chromosome) 55 genes=unique(Table$Chromosome)
50 per_gene_readmap=lapply(genes, function(x) subset(Table, Chromosome==x)) 56 per_gene_readmap=lapply(genes, function(x) subset(Table, Chromosome==x))
51 per_gene_limit=lapply(genes, function(x) c(1, unique(subset(Table, Chromosome==x)$Chrom_length)) ) 57 per_gene_limit=lapply(genes, function(x) c(1, unique(subset(Table, Chromosome==x)$Chrom_length)) )
52 n_genes=length(per_gene_readmap) 58 n_genes=length(per_gene_readmap)
59
53 # second table 60 # second table
54 if (args$extra_plot_method != '') { 61 if (args$extra_plot_method != '') {
55 ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL) 62 ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL)
56 colnames(ExtraTable)[1] <- "Dataset" 63 colnames(ExtraTable)[1] <- "Dataset"
64 dropcol <- c("Strandness", "z.score") # not used by this Rscript and is dropped for backward compatibility
65 Table <- Table[,!(names(Table) %in% dropcol)]
57 if (args$extra_plot_method == "Counts" | args$extra_plot_method=='Size') { 66 if (args$extra_plot_method == "Counts" | args$extra_plot_method=='Size') {
58 ExtraTable <- within(ExtraTable, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1)) 67 ExtraTable <- within(ExtraTable, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1))
59 } 68 }
60 if (args$extra_plot_method == "Counts" | args$extra_plot_method == "Size" | args$extra_plot_method == "Coverage") { 69 if (args$extra_plot_method == "Counts" | args$extra_plot_method == "Size" | args$extra_plot_method == "Coverage") {
61 i = 1 70 i = 1
132 ...) 141 ...)
133 p=combineLimits(p) 142 p=combineLimits(p)
134 } else if (method != "Size") { 143 } else if (method != "Size") {
135 p = xyplot(eval(as.name(method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)), 144 p = xyplot(eval(as.name(method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
136 data=df, 145 data=df,
137 type='p', 146 type= ifelse(method=='Coverage', 'l', 'p'),
138 pch=19, 147 pch=19,
139 cex=0.35, 148 cex=0.35,
140 scales= list(relation="free", x=list(rot=0, cex=0.7, tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)), 149 scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
141 xlab=NULL, main=NULL, ylab=NULL, ylim=ylimits, 150 xlab=NULL, main=NULL, ylab=NULL, ylim=ylimits,
142 as.table=T, 151 as.table=T,
143 origin = 0, 152 origin = 0,
144 horizontal=FALSE, 153 horizontal=FALSE,
145 group=Polarity, 154 group=Polarity,
146 col=c("red","blue"), 155 col=c("red","blue"),
147 par.strip.text = list(cex=0.7), 156 par.strip.text = list(cex=0.7),
148 ...) 157 ...)
158 p=combineLimits(p)
149 } else { 159 } else {
150 p = barchart(Counts~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0, 160 p = barchart(Counts~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0,
151 horizontal=FALSE, 161 horizontal=FALSE,
152 group=Polarity, 162 group=Polarity,
153 stack=TRUE, 163 stack=TRUE,