Mercurial > repos > vmarcon > plot_pca
changeset 0:610e86c430a9 draft default tip
planemo upload commit 0b661bcf940c03e11becd42b3321df9573b591b2
| author | vmarcon |
|---|---|
| date | Mon, 23 Oct 2017 09:34:56 -0400 |
| parents | |
| children | |
| files | LICENSE plot_pca.R plot_pca.xml rainbow.3.txt test-data/decathlon.tsv test-data/output |
| diffstat | 6 files changed, 1421 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/LICENSE Mon Oct 23 09:34:56 2017 -0400 @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/> + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. By contrast, +the GNU General Public License is intended to guarantee your freedom to +share and change all versions of a program--to make sure it remains free +software for all its users. We, the Free Software Foundation, use the +GNU General Public License for most of our software; it applies also to +any other work released this way by its authors. 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Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +<http://www.gnu.org/licenses/>. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +<http://www.gnu.org/philosophy/why-not-lgpl.html>.
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/plot_pca.R Mon Oct 23 09:34:56 2017 -0400 @@ -0,0 +1,421 @@ +#!/usr/bin/env Rscript + +# DEFAULT OPTIONS + +opt = list() +opt$log10 = FALSE +opt$pseudocount = 1e-04 +opt$row_as_variables = FALSE + +suppressPackageStartupMessages(library("optparse")) + +options(stringsAsFactors=F) + +################## +# OPTION PARSING +################## + +option_list <- list( +make_option(c("-i", "--input_matrix"), help="the matrix you want to analyze. Can be stdin"), +make_option(c("-l", "--log10"), action="store_true", default=FALSE, help="apply the log [default=FALSE]"), +make_option(c("-p", "--pseudocount"), type="double", help="specify a pseudocount for the log [default=%default]", default=1e-04), +make_option(c("-m", "--metadata"), help="A list of tsv files with metadata on matrix experiment.\n\t\tThey must be in the format 'file1.tsv,file2.tsv' and contain a key column named 'labExpId'. Can be omitted"), + +make_option(c("--merge_mdata_on"), default="labExpId", + help="[default=%default]"), + +#make_option(c("-o", "--output"), help="additional info you want to put in the output file name", default="out"), +make_option(c("-c", "--color_by"), help="choose the fields in the metadata you want to color by", type='character'), + +make_option(c("--sort_color"), type='character', + help="A field for sorting colors. Can be omitted [default=%default]"), + +make_option(c("-s", "--shape_by"), default=NULL, type="character", help="choose the fields in the metadata you want to shape by"), + +make_option(c("--no_legend"), action="store_true", default=FALSE, + help="Do not show the legend [default=%default]"), + +make_option(c("-r", "--row_as_variables"), action="store_true", help="select this if you want rows as variables [default=%default]", default=FALSE), +make_option(c("-C", "--princomp"), help="choose the principal components you want to plot. With 3 PC it gives a 3d plot [default='PC1,PC2']", default="PC1,PC2"), + +make_option(c("--print_scores"), action="store_true", default=FALSE, + help="Output the resuling PCs as a separate file with the extension PCs.tsv [default=%default]"), + +make_option(c("--print_loadings"), action="store_true", default=FALSE, + help="Output the resulting loadings as a separate file with the extension loadings.tsv [default=%default]"), + +make_option(c("--print_lambdas"), action="store_true", default=FALSE, + help="Output the resulting lambdas (stdev) as a separate file with the extension lambdas.tsv [default=%default]"), + +make_option(c("--biplot"), default=FALSE, action="store_true", + help="If active, the factor of the color is used as grouping factor. + Centroids are computed and the first <top> loadings are plotted wrt to the two specified components [default=%default]"), + +make_option(c("--palette"), default="/users/rg/abreschi/R/palettes/cbbPalette1.15.txt", + help="File with the color palette [default=%default]"), + +make_option(c("--border"), default=FALSE, action="store_true", + help="Black border to dots [default=%default]"), + +make_option(c("--shapes"), + help="File with the shapes [default=%default]"), + +make_option(c("-L", "--labels"), default=NULL, type="character", + help="The metadata field with the labels [default=%default]"), + +make_option(c("-B", "--base_size"), default=16, type='numeric', + help="Base font size [default=%default]"), + +make_option(c("-H", "--height"), default=7, + help="Height of the plot in inches [default=%default]"), + +make_option(c("-W", "--width"), default=7, + help="Width of the plot in inches [default=%default]"), + +make_option(c("-o", "--output"), default="pca.out", + help="output file name [default=%default]"), + +make_option(c("-v", "--verbose"), action='store_true', default=FALSE, + help="verbose output [default=%default]") +) + +parser <- OptionParser(usage = "%prog [options] file", option_list=option_list) +arguments <- parse_args(parser, positional_arguments = TRUE) +opt <- arguments$options + +if (opt$verbose) {print(opt)} +##------------ +## LIBRARIES +##------------ +suppressPackageStartupMessages(library("reshape")) +suppressPackageStartupMessages(library("ggplot2")) +suppressPackageStartupMessages(library("grid")) + + +############### +# BEGIN +############## + +# read input tables +inF = opt$input_matrix; if (opt$input_matrix == "stdin") {inF = file("stdin")} +m = read.table(inF, h=T, sep="\t") +if (opt$verbose) { + cat("Sample of input matrix:\n") + print(head(m[,1:10])) +} + + +# Read the color palette +my_palette = read.table(opt$palette, h=F, comment.char="%", sep="\t")$V1 + +# Read the color ordering +if (is.null(opt$sort_color)) { + sort_color=NULL +}else{ + sort_color = strsplit(opt$sort_color, ",")[[1]] +} + +# Read the shapes +if (!is.null(opt$shapes)) { + my_shapes = read.table(opt$shapes, h=F, comment.char="%")$V1 +} + +# remove potential gene id columns +char_cols <- which(sapply(m, class) == 'character') +if (length(char_cols) == 0) {genes = rownames(m)} +if (length(char_cols) != 0) {genes = m[,char_cols]; m = m[,-(char_cols)]} + +if (opt$verbose) {sprintf("WARNING: column %s is character, so it is removed from the analysis", char_cols)} + +# apply the log if required +if (opt$log10) {m = log10(replace(m, is.na(m), 0) + opt$pseudocount)} + +# apply pca +#if (opt$row_as_variable) { +#m_pca = prcomp(na.omit(m), center=FALSE, scale.=FALSE)} else{ +#m_pca = prcomp(t(na.omit(m)), center=FALSE, scale.=FALSE)} +#Modified by Gaelle Lefort +# apply pca +if (opt$row_as_variable) { +m_pca = prcomp(t(na.omit(m)), center=FALSE, scale.=FALSE) +} else { +m_pca = prcomp(na.omit(m), center=FALSE, scale.=FALSE) +} + + +# Scale the scores for biplot +#scaledScores = sweep(m_pca$x, 2, m_pca$sdev / sqrt(nrow(m_pca$x)), "/") +scaledScores = m_pca$x + +if (opt$verbose) {print(dim(na.omit(m)))} + +# HANDLING METADATA + +# add metadata to pca results, they should be input in the command line in the future +if (is.null(opt$color_by)) {color_by=NULL +}else{color_by = color_by = strsplit(opt$color_by, ",")[[1]]} +if (is.null(opt$shape_by)) {shape_by=NULL +}else{shape_by = strsplit(opt$shape_by, ",")[[1]]} + +# read metadata, one or more table to be merged on labExpId +if (!is.null(opt$metadata)){ + mdata = read.table(opt$metadata, h=T, sep="\t", row.names=NULL, comment.char="", quote=""); + if (opt$merge_mdata_on %in% colnames(mdata)) { + mdata[,opt$merge_mdata_on] <- gsub("[,-]", ".", mdata[,opt$merge_mdata_on]) + } + + if (opt$verbose) {cat('append metadata...')} + + df = merge(as.data.frame(scaledScores), + unique(mdata[c(color_by, shape_by, opt$merge_mdata_on, opt$labels)]), by.x='row.names', by.y=opt$merge_mdata_on, all.x=T) + if (opt$verbose) {cat("DONE\n")} +}else{ + df = as.data.frame(scaledScores) +} + + +if (opt$verbose) {print(head(df))} + +######### +# OUTPUT +######### + +output_name = opt$output + +# Print text outputs if required + +# -- principal components -- +if (opt$print_scores) { + write.table(m_pca$x, sprintf("%s.PCs.tsv", output_name), quote=F, sep="\t") +} + +# -- loadings -- +if (opt$print_loadings) { + write.table(m_pca$rotation, sprintf("%s.loadings.tsv", output_name), quote=F, sep="\t") +} + +# -- lambdas -- +if (opt$print_lambdas) { + perc = round(100*m_pca$sdev/sum(m_pca$sdev), 2) + variances = round(m_pca$sdev^2/sum(m_pca$sdev^2)*100, 2) + out_df = data.frame(lambda=m_pca$sdev, perc=perc, var_perc=variances) + write.table(out_df, sprintf("%s.lambdas.tsv", output_name), quote=F, sep="\t") +} + +# Read the required components +prinComp = strsplit(opt$princomp, ",")[[1]] +prinComp_i = as.numeric(gsub("PC", "", prinComp)) + +# Get a vector with all the variance percentages +variances = round(m_pca$sdev^2/sum(m_pca$sdev^2)*100, 2) + +if (opt$biplot) { + + aggrVar = opt$color_by + + # === Centroids === + + centroids = aggregate ( + formula(sprintf(".~%s", aggrVar)), + df[,c(colnames(df)[grep("^PC", colnames(df))], aggrVar)], + mean + ) + centroidsM = centroids[,-1] + + # === Loadings === + + vecNorm = function(x) {sqrt(sum(x**2))} + + scaledLoadings = sweep(m_pca$rotation, 2, m_pca$sdev * nrow(m_pca$x), "*") + + centroidsNorm = apply(centroidsM[,prinComp], 1, vecNorm) # DIM: number of levels x 1 + loadingsNorm = apply(scaledLoadings[,prinComp], 1, vecNorm) # DIM: number of variables x 1 + + cosine = ( scaledLoadings[,prinComp] %*% t(centroidsM[,prinComp]) ) / (loadingsNorm %*% t(centroidsNorm)) + cosine = setNames(data.frame(cosine), centroids[,1]) + + closest = setNames(melt(apply(1-cosine, 2, rank)), c("variable", aggrVar, "rank")) + write.table( closest, file=sprintf("%s.cosine.tsv", opt$output), quote=F, row.names=F, sep="\t"); + + closest_df = data.frame(merge(closest, scaledLoadings, by.x="variable", by.y="row.names")) + + +} + + + +############# +# PLOT +############# + +# plot parameters +pts = 5 + +l_col = opt$labels +base_size = opt$base_size + +theme_set(theme_bw(base_size = base_size)) +theme_update(legend.text=element_text(size=0.9*base_size), + legend.key.size=unit(0.9*base_size, "points"), + legend.key = element_blank() +) + +top = 30 + + +# Open device for plotting +pdf(sprintf("%s.pdf", output_name), w=opt$width, h=opt$height) + +if (length(prinComp) == 2){ + + geom_params = list() + geom_params$size = pts +# geom_params$alpha = opt$alpha + + mapping = list() + mapping <- modifyList(mapping, aes_string(x=prinComp[1], y=prinComp[2])) + + if (!is.null(opt$color_by)) { + gp_color_by=interaction(df[color_by]) + if (!is.null(opt$sort_color)) { + gp_color_by = factor(gp_color_by, levels=sort_color) + } + mapping = modifyList(mapping, aes_string(color=gp_color_by, order=gp_color_by)) + } else { + gp_color_by=NULL + } + + if (!is.null(opt$shape_by)) { + gp_shape_by=interaction(df[shape_by]) + if (!is.null(opt$sort_shape)) { + gp_shape_by = factor(gp_shape_by, levels=sort_shape) + } + mapping = modifyList(mapping, aes_string(shape=gp_shape_by, order=gp_shape_by)) + } else { + gp_shape_by=NULL + } + +# if (!is.na(opt$shape_by)) {gp_shape_by=interaction(df[shape_by]); +# gp_shape_by <- factor(gp_shape_by, levels=sort(levels(gp_shape_by))) +# mapping = modifyList(mapping, aes_string(shape=S_col)) + + class(mapping) <- "uneval" + + pointLayer <- layer( + geom = "point", + # geom_params = geom_params, + params = geom_params, + mapping = mapping, + stat = "identity", + position = "identity" + ) + + + + + # plotting... + gp = ggplot(df, aes_string(x=prinComp[1],y=prinComp[2])); + + if (opt$biplot) { + gp = gp + geom_point(data=centroids, aes_string(x=prinComp[1], y=prinComp[2], color=opt$color_by), shape=8, size=7) + gp = gp + geom_segment( + data=subset(closest_df, rank <= top), + aes_string(x=0, y=0, xend=prinComp[1], yend=prinComp[2], color=opt$color_by) + ) + } + + + if (opt$border) { + if (!is.null(opt$shape_by)) { + gp = gp + geom_point(aes(shape=gp_shape_by), col='black', size=pts+1.0); + } else { + gp = gp + geom_point(col="black", size=pts+1.0) + } + } + + gp = gp + pointLayer + +# gp = gp + geom_point(aes(color=gp_color_by)) +# gp = gp + geom_point(aes(col=gp_color_by, shape=gp_shape_by), size=pts); +# + gp = gp + labs(title=""); + gp = gp + labs(x=sprintf('%s (%s%%)', prinComp[1], variances[prinComp_i[1]])); + gp = gp + labs(y=sprintf('%s (%s%%)', prinComp[2], variances[prinComp_i[2]])); + + gp = gp + scale_color_manual(name=opt$color_by, values=my_palette) + if (!is.null(opt$shapes)) { + gp = gp + scale_shape_manual(name=opt$shape_by, values=my_shapes); + } + if (opt$no_legend) { + gp = gp + guides(shape=FALSE, color=FALSE) + +} + if (!is.null(opt$labels)) { + gp = gp + geom_text(aes_string(label=l_col), size=pts) + } + + gp +} + + + + +# -------------------- +# +# 3d scatterplot +# +# -------------------- + + +if (length(prinComp) == 3) { + +suppressPackageStartupMessages(library(scatterplot3d)) + +par(xpd=NA, omi=c(0.5, 0.5, 0.5, 1.0)) + +if (!is.na(opt$color_by)) {gp_color=my_palette[interaction(df[color_by])]} else {gp_color="black"} +if (!is.null(opt$shape_by)) {gp_shape_by=interaction(df[shape_by]); +gp_shape_by <- factor(gp_shape_by, levels=sort(intersect(levels(gp_shape_by), gp_shape_by))); gp_shape=my_shapes[gp_shape_by]} else {gp_shape_by=NULL} + +plot3d = scatterplot3d(df[prinComp], + color = gp_color, + pch = gp_shape, + xlab = sprintf('%s (%s%%)', prinComp[1], variances[prinComp_i[1]]), + ylab = sprintf('%s (%s%%)', prinComp[2], variances[prinComp_i[2]]), + zlab = sprintf('%s (%s%%)', prinComp[3], variances[prinComp_i[3]]), + cex.symbols = 1.5, + lab = c(5,4) +) + +# !!! To be removed after the mouse paper !!! +#i=0; for(sample in interaction(df[color_by])) { +#i=i+1; plot3d$points3d(subset(df, General_category == sample, select=prinComp), type='l', col=gp_color[i])} + +if (!is.na(opt$color_by)) { + legend( + x = log(max(df[prinComp[1]])) + 3, +# x = 5, + y = 5.5, + legend = levels(interaction(df[color_by])), + fill = my_palette[seq_along(levels(interaction(df[color_by])))] + ) +} + +if (!is.na(opt$shape_by)) { + legend( +# x = -log(abs(min(df[prinComp[1]]))) - 1.5, + x = -3, + y = 6, +# y = 7.2, + legend = levels(gp_shape_by), + pch = my_shapes[seq_along(levels(gp_shape_by))] + ) +# legend(-log(abs(min(df[prinComp[1]])))+1.5,7.2,levels(gp_shape_by), +# pch=shapes[seq_along(levels(gp_shape_by))]) +} +} + + +dev.off() +q(save='no') +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/plot_pca.xml Mon Oct 23 09:34:56 2017 -0400 @@ -0,0 +1,281 @@ +<!--# Copyright (C) 2017 INRA +# This program is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 3 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program. If not, see http://www.gnu.org/licenses/. +#--> +<tool id="plot_pca" name="Plot PCA" version="1.0.0"> + <description>PCA analysis</description> + <requirements> + <requirement type="package">R</requirement> + <requirement type="package">r-optparse</requirement> + <requirement type="package">r-reshape</requirement> + <requirement type="package">r-ggplot2</requirement> + <requirement type="package">r-gridextra</requirement> + <requirement type="package">r-scatterplot3d</requirement> + </requirements> + <stdio> + <!-- Anything other than zero is an error --> + <exit_code range="1:" level="fatal"/> + <exit_code range=":-1" level="fatal"/> + </stdio> + <command><![CDATA[ + Rscript $__tool_directory__/plot_pca.R + --input_matrix $input_matrix + #if $log_cond.log10: + -l $log_cond.pseudocount + #end if + #if $height + --height $height + #end if + #if $width + --width $width + #end if + #if $output + --output $output + #end if + #if $metadata_cond.metadata: + --metadata + $metadata_cond.input_metadata + #for $i, $s in enumerate( $metadata_cond.series ) + ,${s.input_metadata2} + #end for + #if $metadata_cond.color_by + --color_by $metadata_cond.color_by + #end if + #if $metadata_cond.shape_by + --shape_by $metadata_cond.shape_by + #end if + #end if + --border + --palette=$__tool_directory__/rainbow.3.txt + && + cp *.pdf $outputfile + ]]></command> + <inputs> + <param argument="--input_matrix" type="data" format="csv,tabular" label="Input Matrix"/> + + <conditional name="log_cond"> + <param name="log10" type="boolean" checked="false" truevalue="True" falsevalue="" label="Apply the log10" help="Default=No"/> + <when value="True"> + <param name="pseudocount" type="float" value="1e-04" help="Default=1e-04" /> + </when> + </conditional> + + <conditional name="metadata_cond"> + <param name="metadata" type="boolean" checked="false" truevalue="Yes" falsevalue="" label="Add file with metadata on matrix experiment?" help="must countain a key column named 'labExpId"/> + <when value="Yes"> + <param name="input_metadata" type="data" format="tsv" label="Input Metadata file"/> + <repeat name="series" title="Others Input Metadata files"> + <param name="input_metadata2" type="data" format="tsv" label="Other Input Metadata file"/> + </repeat> + <param argument="--color_by" type="text" label="Choose the fields in the metadata you want to color by" /> + <param argument="--shape_by" type="text" label="Choose the fields in the metadata you want to shape by" /> + </when> + </conditional> + + <param argument="--height" size="20" type="integer" value="7" label="Height of the plot in inches" /> + <param argument="--width" size="20" type="integer" value="7" label="Width of the plot in inches" /> + <param argument="--output" type="text" label="Output name" help="[Optional] Specify the project label for your outputs. By default it will be the name of your input file."/> + </inputs> + <outputs> + <data format="pdf" name="outputfile" label ="#if str($output)=='' then os.path.splitext(str($input_matrix.name))[0] else $output #_PCA.pdf"/> + </outputs> + <tests> + <test> + <param name="input_matrix" value="decathlon.tsv" /> + <conditional name="log_cond"> + <param name="log10" value="True" /> + <param name="pseudocount" value="1e-04" /> + </conditional> + <conditional name="metadata_cond"> + <param name="metadata" value="" /> + </conditional> + <param name="height" value="7" /> + <param name="width" value="7" /> + <param name="output" value="" /> + <output name="outputfile" file="output" compare="sim_size" /> + </test> + </tests> + + <help><![CDATA[ + +======== +Plot PCA +======== + +----------- +Description +----------- + +Plot a Principal Component Analysis (PCA) from a data matrix + +----------- +Input files +----------- + ++---------------------------+----------------+ +| Parameter : num + label | Format | ++===========================+================+ +| 1 : Input matrix | csv,tabular | ++---------------------------+----------------+ + +---------- +Parameters +---------- + +Apply the log 10 + | To normalize your data + | + +(?)Add file with metadata on matrix experiment? + | To ad metadata to the analysis + | + +Input Metadata file + | Must countain a key column named labExpId + | + +Others Metadata files + | + +Choose the fields in the metadata you want to color by + | + +Choose the fields in the metadata you want to shape by + | + +Height of the plot in inches + | default 7 inches + | + +Width of the plot in inches + | default 7 inches + | + +Output name + | Specify the project label for your outputs. By default it will be the name of your input file + | + +------------ +Output files +------------ + +<Input Name>_PCA.pdf + | Pdf file containing your PCA plot + + +------ + +**Authors** +Alessandra Breschi (alessandra.breschi@crg.eu); +Sarah Djebali (sarah.djebali-quelen@inra.fr); +Valentin Marcon (valentin.marcon@inra.fr) + +Contact : sigenae-support@listes.inra.fr + +------------- +Please cite : +------------- + +- (Depending on the help provided you can cite us in acknowledgements) + +Acknowledgements + | We wish to thank : Alessandra Breschi, Sarah Djebali (Centre for Genomic Regulation - http://www.crg.eu/), and Valentin Marcon (Migale platform - http://migale.jouy.inra.fr/) + + + +------ + +.. class:: infomark + +Usage: ./plot_pca.R [options] file + +Options: + -i INPUT_MATRIX, --input_matrix=INPUT_MATRIX + the matrix you want to analyze. Can be stdin + + -l, --log10 + apply the log [default=FALSE] + + -p PSEUDOCOUNT, --pseudocount=PSEUDOCOUNT + specify a pseudocount for the log [default=1e-04] + + -m METADATA, --metadata=METADATA + A list of tsv files with metadata on matrix experiment. + They must be in the format 'file1.tsv,file2.tsv' and contain a key column named 'labExpId'. Can be omitted + + --merge_mdata_on=MERGE_MDATA_ON + [default=labExpId] + + -c COLOR_BY, --color_by=COLOR_BY + choose the fields in the metadata you want to color by + + --sort_color=SORT_COLOR + A field for sorting colors. Can be omitted [default=NULL] + + -s SHAPE_BY, --shape_by=SHAPE_BY + choose the fields in the metadata you want to shape by + + --no_legend + Do not show the legend [default=FALSE] + + -r, --row_as_variables + select this if you want rows as variables [default=FALSE] + + -C PRINCOMP, --princomp=PRINCOMP + choose the principal components you want to plot. With 3 PC it gives a 3d plot [default='PC1,PC2'] + + --print_scores + Output the resuling PCs as a separate file with the extension PCs.tsv [default=FALSE] + + --print_loadings + Output the resulting loadings as a separate file with the extension loadings.tsv [default=FALSE] + + --print_lambdas + Output the resulting lambdas (stdev) as a separate file with the extension lambdas.tsv [default=FALSE] + + --biplot + If active, the factor of the color is used as grouping factor. + Centroids are computed and the first <top> loadings are plotted wrt to the two specified components [default=FALSE] + + --palette=PALETTE + File with the color palette [default=/users/rg/abreschi/R/palettes/cbbPalette1.15.txt] + + --border + Black border to dots [default=FALSE] + + --shapes=SHAPES + File with the shapes [default=NULL] + + -L LABELS, --labels=LABELS + The metadata field with the labels [default=NULL] + + -B BASE_SIZE, --base_size=BASE_SIZE + Base font size [default=16] + + -H HEIGHT, --height=HEIGHT + Height of the plot in inches [default=7] + + -W WIDTH, --width=WIDTH + Width of the plot in inches [default=7] + + -o OUTPUT, --output=OUTPUT + output file name [default=pca.out] + + -v, --verbose + verbose output [default=FALSE] + + -h, --help + Show this help message and exit + + ]]></help> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/rainbow.3.txt Mon Oct 23 09:34:56 2017 -0400 @@ -0,0 +1,3 @@ +#FF0000FF +#00FF00FF +#0000FFFF
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/decathlon.tsv Mon Oct 23 09:34:56 2017 -0400 @@ -0,0 +1,42 @@ +"name" "100m" "Long.jump" "Shot.put" "High.jump" "400m" "110m.hurdle" "Discus" "Pole.vault" "Javeline" "1500m" +"SEBRLE" 11.04 7.58 14.83 2.07 49.81 14.69 43.75 5.02 63.19 291.7 +"CLAY" 10.76 7.4 14.26 1.86 49.37 14.05 50.72 4.92 60.15 301.5 +"KARPOV" 11.02 7.3 14.77 2.04 48.37 14.09 48.95 4.92 50.31 300.2 +"BERNARD" 11.02 7.23 14.25 1.92 48.93 14.99 40.87 5.32 62.77 280.1 +"YURKOV" 11.34 7.09 15.19 2.1 50.42 15.31 46.26 4.72 63.44 276.4 +"WARNERS" 11.11 7.6 14.31 1.98 48.68 14.23 41.1 4.92 51.77 278.1 +"ZSIVOCZKY" 11.13 7.3 13.48 2.01 48.62 14.17 45.67 4.42 55.37 268 +"McMULLEN" 10.83 7.31 13.76 2.13 49.91 14.38 44.41 4.42 56.37 285.1 +"MARTINEAU" 11.64 6.81 14.57 1.95 50.14 14.93 47.6 4.92 52.33 262.1 +"HERNU" 11.37 7.56 14.41 1.86 51.1 15.06 44.99 4.82 57.19 285.1 +"BARRAS" 11.33 6.97 14.09 1.95 49.48 14.48 42.1 4.72 55.4 282 +"NOOL" 11.33 7.27 12.68 1.98 49.2 15.29 37.92 4.62 57.44 266.6 +"BOURGUIGNON" 11.36 6.8 13.46 1.86 51.16 15.67 40.49 5.02 54.68 291.7 +"Sebrle" 10.85 7.84 16.36 2.12 48.36 14.05 48.72 5 70.52 280.01 +"Clay" 10.44 7.96 15.23 2.06 49.19 14.13 50.11 4.9 69.71 282 +"Karpov" 10.5 7.81 15.93 2.09 46.81 13.97 51.65 4.6 55.54 278.11 +"Macey" 10.89 7.47 15.73 2.15 48.97 14.56 48.34 4.4 58.46 265.42 +"Warners" 10.62 7.74 14.48 1.97 47.97 14.01 43.73 4.9 55.39 278.05 +"Zsivoczky" 10.91 7.14 15.31 2.12 49.4 14.95 45.62 4.7 63.45 269.54 +"Hernu" 10.97 7.19 14.65 2.03 48.73 14.25 44.72 4.8 57.76 264.35 +"Nool" 10.8 7.53 14.26 1.88 48.81 14.8 42.05 5.4 61.33 276.33 +"Bernard" 10.69 7.48 14.8 2.12 49.13 14.17 44.75 4.4 55.27 276.31 +"Schwarzl" 10.98 7.49 14.01 1.94 49.76 14.25 42.43 5.1 56.32 273.56 +"Pogorelov" 10.95 7.31 15.1 2.06 50.79 14.21 44.6 5 53.45 287.63 +"Schoenbeck" 10.9 7.3 14.77 1.88 50.3 14.34 44.41 5 60.89 278.82 +"Barras" 11.14 6.99 14.91 1.94 49.41 14.37 44.83 4.6 64.55 267.09 +"Smith" 10.85 6.81 15.24 1.91 49.27 14.01 49.02 4.2 61.52 272.74 +"Averyanov" 10.55 7.34 14.44 1.94 49.72 14.39 39.88 4.8 54.51 271.02 +"Ojaniemi" 10.68 7.5 14.97 1.94 49.12 15.01 40.35 4.6 59.26 275.71 +"Smirnov" 10.89 7.07 13.88 1.94 49.11 14.77 42.47 4.7 60.88 263.31 +"Qi" 11.06 7.34 13.55 1.97 49.65 14.78 45.13 4.5 60.79 272.63 +"Drews" 10.87 7.38 13.07 1.88 48.51 14.01 40.11 5 51.53 274.21 +"Parkhomenko" 11.14 6.61 15.69 2.03 51.04 14.88 41.9 4.8 65.82 277.94 +"Terek" 10.92 6.94 15.15 1.94 49.56 15.12 45.62 5.3 50.62 290.36 +"Gomez" 11.08 7.26 14.57 1.85 48.61 14.41 40.95 4.4 60.71 269.7 +"Turi" 11.08 6.91 13.62 2.03 51.67 14.26 39.83 4.8 59.34 290.01 +"Lorenzo" 11.1 7.03 13.22 1.85 49.34 15.38 40.22 4.5 58.36 263.08 +"Karlivans" 11.33 7.26 13.3 1.97 50.54 14.98 43.34 4.5 52.92 278.67 +"Korkizoglou" 10.86 7.07 14.81 1.94 51.16 14.96 46.07 4.7 53.05 317 +"Uldal" 11.23 6.99 13.53 1.85 50.95 15.09 43.01 4.5 60 281.7 +"Casarsa" 11.36 6.68 14.92 1.94 53.2 15.39 48.66 4.4 58.62 296.12