Mercurial > repos > proteore > proteore_heatmap_visualization
changeset 0:edbb84a94a36 draft
planemo upload commit bdd7e8a1f08c11db2a9f1b6db5535c6d32153b2b
| author | proteore |
|---|---|
| date | Tue, 18 Dec 2018 09:58:49 -0500 |
| parents | |
| children | b8a5139cf5b9 |
| files | heatmap.xml heatmap_viz.R test-data/dat.nucl.norm.imputed.tsv test-data/heatmap.html |
| diffstat | 4 files changed, 678 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/heatmap.xml Tue Dec 18 09:58:49 2018 -0500 @@ -0,0 +1,168 @@ +<tool id="heatmap" name="HeatMap" version="2018.12.12"> + <description></description> + <requirements> + <requirement type="package" version="4.7.1">r-plotly</requirement> + <requirement type="package" version="0.14.1">r-heatmaply</requirement> + <requirement type="package" version="2.1.1">phantomjs</requirement> + <requirement type="package" version="2.2.1">pandoc</requirement> + </requirements> + <command detect_errors="exit_code"><![CDATA[ + Rscript $__tool_directory__/heatmap_viz.R + --input='$file' + --output="$file.name" + --type='$output_type' + --cols='$select_data_columns.cols' + --row_names=$rownames + --header='$header' + --col_text_angle='$angle_col' + --dist="$distance" + --clust="$clustering" + --dendrogram="$dendrogram" + + ]]></command> + <inputs> + <param name="file" type="data" format="txt,tabular" label="Select your file (table)" help="" /> + <param name="header" type="boolean" checked="true" truevalue="true" falsevalue="false" label="Does your file contain a header?" /> + <conditional name="select_data_columns"> + <param name="enter_cols" type="select" label="Select columns or a range of columns containing expression values"> + <option value="cols_number">Select columns to be used one by one</option> + <option value="cols_range">Select a range of columns to be used</option> + </param> + <when value="cols_number"> + <param name="cols" type="text" label="Enter column number (separated by a comma)" help="For example : c3,c5,c7"/> + </when> + <when value="cols_range"> + <param name="cols" type="text" label="Enter a range of column number, first and last column separated by ':'" help="For example : c2:c7"/> + </when> + </conditional> + <param name="rownames" type="text" value="c1" label="Enter column number containing row labels" help="for example : c1 if labels are in column n°1"/> + <param type="integer" name="angle_col" label="Angle of column labels" value="0" min="-90" max="90" /> + <param name="clustering" type="select" label="Clustering method" value="average"> + <option value="ward.D">Ward</option> + <option value="ward.D2">Ward2</option> + <option value="single">Single linkage (nearest neighbor)</option> + <option value="complete">Complete linkage (farthest neighbor)</option> + <option value="average" selected="true">Group average linkage (UPGMA)</option> + <option value="mcquitty">Simple average method (WPGMA)</option> + <!--option value="median">Median (WPGMC)</option> + <option value="centroid">Centroid (UPGMC)</option--> + </param> + <param name="distance" type="select" label="Distance measurement method" value="euclidean"> + <option value="euclidean" selected="true">Euclidean</option> + <option value="pearson" selected="true">Pearson</option> + <option value="spearman">Spearman</option> + <option value="kendall">Kendall</option> + <option value="maximum">Maximum</option> + <option value="manhattan">Manhattan</option> + <option value="canberra">Canberra</option> + <option value="binary">Binary</option> + <option value="minkowski">Minkowski</option> + </param> + <param name="dendrogram" type="select" label="Apply clustering on :" value="both"> + <option value="row">Rows</option> + <option value="column">Columns</option> + <option value="both" selected="true">Rows and columns</option> + <option value="none">None</option> + </param> + + <param name="output_type" type="select" label="Select output format"> + <option value="html">html</option> + <option value="pdf">pdf</option> + <option value="jpeg">jpeg</option> + <option value="png">png</option> + </param> + + </inputs> + <outputs> + <data name="output" format="html"> + <discover_datasets pattern="(?P<designation>.+)\.html" ext="html" visible="true" assign_primary_output="true"/> + <filter>output_type=="html"</filter> + </data> + <data name="pdf" format="pdf"> + <discover_datasets pattern="(?P<designation>.+)\.pdf" ext="pdf" visible="true" assign_primary_output="true"/> + <filter>output_type=="pdf"</filter> + </data> + <data name="jpeg" format="jpg"> + <discover_datasets pattern="(?P<designation>.+)\.jpg" ext="jpg" visible="true" assign_primary_output="true"/> + <filter>output_type=="jpeg"</filter> + </data> + <data name="png" format="png"> + <discover_datasets pattern="(?P<designation>.+)\.png" ext="png" visible="true" assign_primary_output="true"/> + <filter>output_type=="png"</filter> + </data> + </outputs> + <tests> + <test> + <output name="output" file="heatmap.html"/> + </test> + </tests> + <help><![CDATA[ +**Description** + +This tool allows users to generate, cluster and visualize expression-based heat maps from transcriptomic, proteomic and metabolomic experiments. +It is based on heatmaply, an R package for easily creating interactive cluster heatmaps (see reference below) + +----- + +**Input** + +A file (tab-delimited) having a column with labels (e.g. a gene name, Uniprot accession number...) and colums with numerical value (intensities) for clustering. +See table below for an example input file + +.. csv-table:: example of input file + :header: "Uniprot","iBAQ_CTR1","iBAQ_CTR2","iBAQ_CTR3","iBAQ_pTCN1","iBAQ_pTCN2","iBAQ_pTCN3" + + + "Q49AN9",17.4091970440807,16.0474907255521,14.9687330755858,21.8454060245779,18.9468529040903,21.2330797498008 + "O00148",14.1001686145694,14.806777888004,15.3555560564928,17.2942797505583,18.2106568817514,16.9479095182613 + "F5H6E2",15.0235503328855,16.6142578028388,20.5969569088489,14.6615767253835,17.9752549753108,20.4023495267791 + "E9PPW7",18.0770953690935,15.312218369812,13.8048301075204,17.5522130063356,15.9664520099065,15.1597932646987 + "O00483",17.4188205774495,16.783665086968,15.1589556127476,19.7398973660168,20.8648965533665,20.1781898785682 + "O00571",12.9049717044645,16.717296441372,13.8708732177805,19.8879681981565,21.0815521014477,17.4710040202845 + +----- + +**Parameters** + +"Select columns or a range of columns containing expression values": choose the columns to use to perform clustering and to create the heatmap. +You can enter specific column number (e.g. c2,c5 will create a heatmap for column 2 and 5 corresponding to condition from the example file above ) or a range of columns to use (e.g. c2:c7 will consider all replicates of each condition in the example above)). + +"Enter column number containing row labels": enter the column number containing the rows labels (e.g. "c1" in the example above). + +"Angle of column labels": In case of long label name, you might want to incline the column labels for practical display. + +"Clustering method": methods for computing hierarchical clustering (six available) + +"Distance measurement method": function used to compute the distance (dissimilarity) between both rows and columns (nine available). The options "pearson", "spearman" and "kendall" can +be used to use correlation-based clustering. + +----- + +**Output** + +Default output is html; it allows browsing the heatmap in an interactive way (of note: for large file, display and interactivity can be altered) +pdf, jpeg or png format are propsoed for static output. + +----- + +.. class:: infomark + +**Authors** +Galili T, O'Callaghan A, Sidi J, Sievert C. heatmaply: an R package for creating interactive cluster heatmaps for online publishing. Bioinformatics. 2018. 34(9):1600-1602. doi: 10.1093/bioinformatics/btx657. PubMed PMID: 29069305 + +----- + +.. class:: infomark + +**Galaxy integration** + +David Christiany, Florence Combes, Yves Vandenbrouck CEA, INSERM, CNRS, Grenoble-Alpes University, BIG Institute, FR + +Sandra Dérozier, Olivier Rué, Christophe Caron, Valentin Loux INRA, Paris-Saclay University, MAIAGE Unit, Migale Bioinformatics platform, FR + +This work has been partially funded through the French National Agency for Research (ANR) IFB project. + +Contact support@proteore.org for any questions or concerns about the Galaxy implementation of this tool. + + ]]></help> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/heatmap_viz.R Tue Dec 18 09:58:49 2018 -0500 @@ -0,0 +1,172 @@ +#!/usr/bin/Rscript + +suppressMessages(library('plotly',quietly = T)) +suppressMessages(library('heatmaply',quietly = T)) + +#packageVersion('plotly') + +get_args <- function(){ + + ## Collect arguments + args <- commandArgs(TRUE) + + ## Default setting when no arguments passed + if(length(args) < 1) { + args <- c("--help") + } + + ## Help section + if("--help" %in% args) { + cat("Pathview R script + Arguments: + --help Print this test + --input path of the input file (must contains a colum of uniprot and/or geneID accession number) + --output Output file + --type type of output file, could be html, pdf, jpg or png + --cols Columns to use for heatmap, exemple : '3:8' to use columns from the third to the 8th + --row_names Column which contains row names + --header True or False + --col_text_angle Angle of columns label ; from -90 to 90 degres + --dist_fun function used to compute the distance + + Example: + ./heatmap_viz.R --input='dat.nucl.norm.imputed.tsv' --output='heatmap.html' --cols='3:8' --row_names='2' --header=TRUE --col_text_angle=0 \n\n") + + q(save="no") + } + + parseArgs <- function(x) strsplit(sub("^--", "", x), "=") + argsDF <- as.data.frame(do.call("rbind", parseArgs(args))) + args <- as.list(as.character(argsDF$V2)) + names(args) <- argsDF$V1 + + return(args) +} + +read_file <- function(path,header){ + file <- try(read.csv(path,header=header, sep="\t",stringsAsFactors = FALSE, quote="",fill=TRUE,check.names = F),silent=TRUE) + if (inherits(file,"try-error")){ + stop("File not found !") + }else{ + return(file) + } +} + +#convert a string to boolean +str2bool <- function(x){ + if (any(is.element(c("t","true"),tolower(x)))){ + return (TRUE) + }else if (any(is.element(c("f","false"),tolower(x)))){ + return (FALSE) + }else{ + return(NULL) + } +} + +#remove remaining quote +#only keep usefull columns +#remove lines with at least one empty cell in a matrix between two defined columns +clean_df <- function(mat,cols,rownames_col){ + uto = mat[,cols] + uto <- as.data.frame(apply(uto,c(1,2),function(x) gsub(",",".",x))) + uto <- as.data.frame(apply(uto,c(1,2),function(x) {ifelse(is.character(x),as.numeric(x),x)})) + rownames(uto) <- mat[,rownames_col] + #bad_lines <- which(apply(uto, 1, function(x) any(is.na(x)))) + #if (length(bad_lines) > 0) { + # uto <- uto[- bad_lines,] + # print(paste("lines",bad_lines, "has been removed: at least one non numeric content")) + #} + return(uto) +} + +get_cols <-function(input_cols) { + input_cols <- gsub("c","",input_cols) + if (grepl(":",input_cols)) { + first_col=unlist(strsplit(input_cols,":"))[1] + last_col=unlist(strsplit(input_cols,":"))[2] + cols=first_col:last_col + } else { + cols = as.integer(unlist(strsplit(input_cols,","))) + } + return(cols) +} + +#get args +args <- get_args() + +#save(args,file="/home/dchristiany/proteore_project/ProteoRE/tools/heatmap_viz/args.rda") +#load("/home/dchristiany/proteore_project/ProteoRE/tools/heatmap_viz/args.rda") + +header=str2bool(args$header) +output <- rapply(strsplit(args$output,"\\."),c) #remove extension +output <- paste(output[1:length(output)-1],collapse=".") +output <- paste(output,args$type,sep=".") +cols = get_cols(args$cols) +rownames_col = as.integer(gsub("c","",args$row_names)) +if (length(cols) <=1 ){ + stop("You need several colums to build a heatmap") +} +dist=args$dist +clust=args$clust +dendrogram=args$dendrogram + +#cleaning data +uto <- read_file(args$input,header) +uto <- clean_df(uto,cols,rownames_col) +uto <- uto[rowSums(is.na(uto)) != ncol(uto), ] #remove emptylines + +if (header) { + col_names = names(data) +} else { + col_names = cols +} + +#building heatmap +if (dist %in% c("pearson","spearman","kendall")){ + heatmaply(uto, file=output, margins=c(100,50,NA,0), plot_method="plotly", labRow = rownames(uto), labCol = col_names, distfun=dist, + hclust_method = clust, dendrogram = dendrogram, grid_gap = 0,cexCol = 1, column_text_angle = as.numeric(args$col_text_angle), + width = 1000, height=1000, colors = c('blue','green','yellow','red')) +} else { + heatmaply(uto, file=output, margins=c(100,50,NA,0), plot_method="plotly", labRow = rownames(uto), labCol = col_names, dist_method = dist, + hclust_method = clust, dendrogram = dendrogram, grid_gap = 0,cexCol = 1, column_text_angle = as.numeric(args$col_text_angle), + width = 1000, height=1000, colors = c('blue','green','yellow','red')) +} + +####heatmaply + +simulateExprData <- function(n, n0, p, rho0, rho1){ row + # n: total number of subjects + # n0: number of subjects with exposure 0 + # n1: number of subjects with exposure 1 + # p: number of genes + # rho0: rho between Z_i and Z_j for subjects with exposure 0 + # rho1: rho between Z_i and Z_j for subjects with exposure 1 + + # Simulate gene expression values according to exposure 0 or 1, + # according to a centered multivariate normal distribution with + # covariance between Z_i and Z_j being rho^|i-j| + n1 <- n - n0 + times <- 1:p + H <- abs(outer(times, times, "-")) + V0 <- rho0^H + V1 <- rho1^H + + # rows are people, columns are genes + genes0 <- MASS::mvrnorm(n = n0, mu = rep(0,p), Sigma = V0) + genes1 <- MASS::mvrnorm(n = n1, mu = rep(0,p), Sigma = V1) + genes <- rbind(genes0,genes1) + return(genes) +} + +#genes <- simulateExprData(n = 50, n0 = 25, p = 100, rho0 = 0.01, rho1 = 0.95) + +#heatmaply(genes, k_row = 2, k_col = 2) + +#heatmaply(cor(genes), k_row = 2, k_col = 2) + + + + + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/dat.nucl.norm.imputed.tsv Tue Dec 18 09:58:49 2018 -0500 @@ -0,0 +1,318 @@ +id Uniprot iBAQ_CTR1 iBAQ_CTR2 iBAQ_CTR3 iBAQ_pTCN1 iBAQ_pTCN2 iBAQ_pTCN3 +85 Q49AN9 17.4091970440807 16.0474907255521 14.9687330755858 21.8454060245779 18.9468529040903 21.2330797498008 +89 O00148 14.1001686145694 14.806777888004 15.3555560564928 17.2942797505583 18.2106568817514 16.9479095182613 +90 F5H6E2 15.0235503328855 16.6142578028388 20.5969569088489 14.6615767253835 17.9752549753108 20.4023495267791 +92 E9PPW7 18.0770953690935 15.312218369812 13.8048301075204 17.5522130063356 15.9664520099065 15.1597932646987 +101 O00483 17.4188205774495 16.783665086968 15.1589556127476 19.7398973660168 20.8648965533665 20.1781898785682 +105 O00571 12.9049717044645 16.717296441372 13.8708732177805 19.8879681981565 21.0815521014477 17.4710040202845 +121 O14880 15.7795152357562 16.9056638034428 13.337884572062 17.7044082430845 18.2623291335539 15.6013730432451 +131 O15020 13.2364391435825 16.0875734675595 17.3471072965076 11.3932084948267 17.5224254853992 16.0210381525735 +153 O43172 14.0986553604854 14.9471566023657 14.6745546404104 20.0511708977192 20.4174260826947 17.9102233324039 +154 Q5SZU1 14.8343706352117 14.9336932868586 15.863517960295 16.5553115638733 13.2384247130195 15.6278162199574 +155 O43181 16.9585411843144 18.0253414246133 14.9688011176101 18.4506581478283 18.060715749432 17.1508218902826 +162 O43395 12.7815915377713 13.2570182327942 14.2151159490732 18.7982994745559 19.0606274400876 17.2081917897096 +170 O43707 14.4053518406046 14.9335246225864 16.7473467820106 13.9490316421179 12.6512953774468 12.488509829076 +172 O43795 16.6433848083358 15.6311118029749 20.0692252954892 14.1953551525139 16.1740085549157 19.5449370166335 +173 O43809 18.8780918275901 15.5053991792138 10.6705596934982 20.0325214098905 19.0562345939939 18.8788858733645 +179 O43920 17.8555846173049 16.0317021406993 15.4193073529273 17.0748503358331 18.6638138225965 15.2226042707806 +198 C9JZR2 12.7604492273804 15.1102454594255 13.2719163803705 14.2208765008612 16.2566097942392 16.1902621154649 +212 O75152 15.6680820455343 15.0519438286799 11.6759710588754 17.1958169834068 18.1627806617006 17.7637389118576 +215 O75251 16.0380636771286 17.3118540988743 14.8408713638196 18.2933996427914 19.2469406522803 17.7901518813423 +216 O75306 17.7731476104228 17.0436820947162 14.3216198760797 18.0682714348397 17.7038323287087 17.4649529913645 +220 O75369 10.5809642077475 15.1397204878621 14.9763339043522 14.4145798670977 13.0731660922891 10.2481720848799 +229 O75489 17.9752051061699 18.5422711615252 15.8278574543733 17.7647633731306 19.0794616174147 14.6897924274007 +234 O75533 10.7492978788409 11.6906933545874 12.3558422513063 16.0541183067786 18.1338889547966 18.1993226892225 +239 O75643 9.56772460294106 14.5115371196252 12.6720983186065 19.6873642615915 19.968822501587 19.1004765946838 +242 O75746 17.9078927655008 11.3730435111001 10.0131616287334 18.185826994594 13.1691675113752 15.1221180214157 +256 O94776 11.3490449754863 13.197432796574 11.5083281047808 14.5931066465682 16.4802205283196 16.5456932336907 +260 O94832 16.7310585463838 17.2925285377812 19.8521284451617 14.8901614386487 18.1901635960251 19.1007398885939 +265 O94906 14.6213840503359 13.6515629350167 9.1203482682031 18.6422967033089 19.6520809706827 18.5888550328822 +273 O95168 20.5206925179917 20.8313406769694 16.0118017974777 17.8571177393245 20.8185612151699 19.4884749760408 +280 A0A087WXC5 18.2572586904791 18.4546534154334 15.203018002337 19.220193815815 19.5429473866248 14.1031742766836 +286 O95425 14.8220020167805 14.4200178489881 18.0635120378048 16.0513169608008 14.8920412166631 16.966836273813 +300 P00403 19.0735282785645 17.7464110488726 17.4028764600704 17.9152591108248 17.7078602604404 17.7924135731373 +306 P02545 13.5624248927807 13.5988458131129 15.373527755546 17.2622702956547 17.0214060903224 15.5358419795327 +312 P04637 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