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comparison RNAseqDataAnnotation/RNAseqDataAnnotation.R @ 12:30506ce512f0 draft

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date Thu, 20 Nov 2014 03:26:52 -0500
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11:90a12c339d99 12:30506ce512f0
1 #Author : keime / lornage
2 #Date : 2014/11
3
4
5 ########################################################################################################
6 #This function concatenates htseq-count result files, normalizes data and annotates data using Ensembl annotations
7
8 #arguments
9 #path2htseqfiles : path to htseq-count result files
10 #samplenamefile : path ta a tabulated text file with 2 columns : 1. File name 2. Sample names and an header
11 #Species : latin name of the species
12 #ensversion : version of Ensembl to use
13 #fileout : .txt file containing for each library ; gene id, raw read counts, normalized data as well as normalized data/gene length
14 #conversionensembleversion : tab-delimited file allowing conversion of the Ensembl version to the host
15 # (Column1 : Version Column2 : Host)
16 #conversionensemblname : tab-delimited file allowing conversion of species name to the name of the Ensembl dataset to use
17 # (Column1 : Specie Column2 : Dataset)
18
19 #output : a data.frame with the following columns :
20 #ensembl gene id
21 #raw read counts for each library (one column per library)
22 #normalized data for each library (one column per library)
23 #normalized data divided by gene length for each library (one column per library)
24 #Gene name
25 #Description
26
27 #require : biomaRt and DESeq2 Bioconductor packages / package plyr1.8.1
28
29 #Methods :
30 #Considering that the resulting files of HTSeq-count have 5 lines of comments in the end
31 #Normalization is performed using the method described in Genome Biology 2010;11(10):R106
32 #and implemented in the DESeq2 Bioconductor package
33 #Gene length correspond to the median of the size of all transcripts corresponding to this gene
34 #########################################################################################################
35
36
37
38 RNAseqDataAnnotation = function(path2htseqfiles, samplenamefile, Species, ensversion, fileout, conversionensemblversion, conversionensemblname){
39
40 #Create a list with the file names in path2htseqfiles
41 sampleFiles=list.files(path2htseqfiles)
42 sampleFiles=strsplit(sampleFiles,".txt")
43 #_noSpikes_htseq
44 nfiles=length(sampleFiles)
45
46 #Read the data in samplenamefile. Create a data frame establishing the correspondence between file names and sample names
47 corresp = read.table(samplenamefile,header=T,sep="\t",colClasses=c("character","character"))
48 corresp$File = strsplit(corresp$File,".fastq.gz")
49
50 #Create a string vector called libnames that contains the name of the samples in the same order as in sampleFiles
51 libnames=rep("",nfiles)
52 for (i in 1:nfiles){
53 libnames[i]=corresp$Sample_name[corresp$File==sampleFiles[[i]]]
54 }
55
56 #For all files located in path2htseqfiles read the corresponding file into R
57 library(plyr)
58 datalist = list()
59 for(i in 1:nfiles){
60 rawdata=read.table(paste(paste(path2htseqfiles,sampleFiles[i],sep="/"),"txt",sep="."))
61 #noSpikes_htseq.
62 nbrrows=nrow(rawdata)
63 datalist[[i]]=rawdata[1:(nbrrows-5), ] # skip the last 5 lines of HTSeq-count files
64 colnames(datalist[[i]]) = c("ID",libnames[i])
65 }
66
67 #Join all the files in a data.frame called datafile with rownames = gene id
68 datafile = join_all(datalist, by = "ID", type = "left", match = "all")
69
70 #Calculate the number of geneID pro file
71 nbID=data.frame(rep("",nfiles))
72 for(i in 1:nfiles){
73 nbID[,i]=nrow(datalist[[i]])
74 }
75 totalnbID=apply((nbID[,1:4]),1,sum)
76
77 #Verify that all the files contain the same gene ID
78 if (nrow(datafile)*4==totalnbID[1]){
79
80 #Suppress genes not expressed in all samples
81 datafile = datafile[apply(datafile[,2:(nfiles+1)],1,sum)!=0,]
82 row.names(datafile)=datafile[,1]
83 data=datafile[,-1]
84
85 #Number of libraries
86 nblib= dim(data)[2]
87 #Determine Data + normalization if the specie is not known
88 if (Species==""){
89 #Normalized data calculation
90 nbcol = dim(data)[2] #nb of column in the data.frame
91 library(DESeq2)
92 conds = factor(1:nblib)
93 design = data.frame(Condition=conds)
94 dds = DESeqDataSetFromMatrix(countData=data, colData=design, design=~Condition)
95 dds = estimateSizeFactors(dds)
96 datanorm = t(t(data)/sizeFactors(dds))
97
98 #Data + normalization
99 dataall = data.frame(row.names(datafile), data, datanorm )
100
101 #Renames columns
102 colnames(dataall) = c("Ensembl gene id", paste(libnames,"(raw read counts)"), paste(libnames,"(normalized)"))
103 write.table(dataall, file=fileout, sep="\t", quote=F, row.names=F)
104 }
105
106 #Determine Data + normalization + annotation if the specie is known
107 else{
108 #Add annotations and calculate gene length
109 library(biomaRt)
110
111 #Convert Ensembl version to host
112 conversionfile = read.table(conversionensemblversion,header=T,sep="\t",colClasses=c("numeric","character"))
113 correspondingdate = conversionfile[conversionfile$Version == ensversion, 2]
114 host = paste(correspondingdate, ".archive.ensembl.org/biomart/martservice/", sep="")
115
116 #Convert species name to the name of the corresponding bmdataset
117 conversion = read.table(conversionensemblname,header=T,sep="\t",colClasses=c("character","character"))
118 bmdataset = conversion[conversion$Specie == Species, 2]
119 ensembl=useMart("ENSEMBL_MART_ENSEMBL", host=host, dataset=bmdataset)
120 if (ensversion<=75){
121 annotation1 = getBM(attributes=c("ensembl_gene_id","external_gene_id","description", "ensembl_transcript_id","exon_chrom_start","exon_chrom_end"),filters="ensembl_gene_id", values=rownames(data), mart=ensembl)
122 }
123 else{
124 annotation1 = getBM(attributes=c("ensembl_gene_id","external_gene_name","description", "ensembl_transcript_id","exon_chrom_start","exon_chrom_end"),filters="ensembl_gene_id", values=rownames(data), mart=ensembl)
125 }
126
127 #because all the annotations are not always found in a first step
128 not = rownames(data)[!rownames(data) %in% unique(annotation1$ensembl_gene_id)]
129 if (length(not) !=0){
130 annotationnot = getBM(attributes=c("ensembl_gene_id","external_gene_id","description", "ensembl_transcript_id","exon_chrom_start","exon_chrom_end"), filters="ensembl_gene_id", values=not, mart=ensembl)
131 annotation = rbind(annotation1, annotationnot)
132 }
133 else{
134 annotation = annotation1
135 }
136
137 #Exon length
138 ensinfos.exlen = data.frame(annotation$ensembl_gene_id, annotation$ensembl_transcript_id, abs(annotation$exon_chrom_start - annotation$exon_chrom_end)+1)
139 colnames(ensinfos.exlen) = c("ensembl_gene_id", "ensembl_transcript_id", "exon_length")
140
141 #Transcript length
142 tlen = tapply(ensinfos.exlen$exon_length, ensinfos.exlen$ensembl_transcript_id, sum)
143 tlen.gene = merge(tlen, unique(ensinfos.exlen[,1:2]), by.x="row.names", by.y="ensembl_transcript_id")
144 colnames(tlen.gene) = c("ensembl_transcript_id", "transcript_length","ensembl_gene_id")
145
146 #Gene length = median of the size of all transcripts corresponding to this gene
147 glen = tapply(tlen.gene$transcript_length, tlen.gene$ensembl_gene_id, median)
148
149 #Data with gene length
150 datalen = merge(data, glen, by="row.names")
151 colnames(datalen) = c("Ensembl_gene_id",colnames(data), "Gene_length")
152
153 #Data with annotations and gene length
154 annotationgene = unique(annotation[,1:3])
155 dataannot = merge(datalen, annotationgene, by.x="Ensembl_gene_id", by.y="ensembl_gene_id")
156
157 #To keep only the first part of the gene description (before [)
158 tmpdesc = strsplit(as.character(dataannot$description),"[", fixed=T)
159 f = function(l){
160 if (length(l)>=1){
161 return(l[[1]])
162 }
163 else{
164 return("")
165 }
166 }
167 tmpdescok = unlist(lapply(tmpdesc, f))
168 dataannot$description = tmpdescok
169
170 #Normalized data calculation
171 nbcol = dim(dataannot)[2] #nb of column in the data.frame
172 library(DESeq2)
173 conds = factor(1:nblib)
174 design = data.frame(Condition=conds)
175 dds = DESeqDataSetFromMatrix(countData=dataannot[,-c(1,nbcol,nbcol-1,nbcol-2)], colData=design, design=~Condition)
176 dds = estimateSizeFactors(dds)
177 datanorm = t(t(dataannot[,-c(1,nbcol,nbcol-1,nbcol-2)])/sizeFactors(dds))
178
179 #Normalized data adjusted for gene length (normalized data / gene length)
180 rpkn = datanorm / (as.vector(dataannot[,nbcol-2]/1000 ))
181
182 #Data + annotations + rpkn
183 dataall = data.frame(dataannot[,-c(nbcol,nbcol-1,nbcol-2)] , datanorm, rpkn, dataannot[,c(nbcol-1,nbcol)] )
184
185 #Renames columns
186 colnames(dataall) = c("Ensembl gene id", paste(libnames,"(raw read counts)"), paste(libnames,"(normalized)"), paste(libnames,"(normalized and divided by gene length in kb)"), "Gene name", "Description")
187 write.table(dataall, file=fileout, sep="\t", quote=F, row.names=F)
188
189 #Return(dataall)
190
191 }
192 }
193 else{
194 print("The files are not the same length")
195 }
196 }
197
198 args <- commandArgs(trailingOnly = TRUE)
199 print(args)
200
201 RNAseqDataAnnotation(args[1], args[2],args[3], args[4], args[5], args[6], args[7])
202
203 #R --slave --vanilla --verbose --file=/home/lornage/Bureau/Pour_galaxy/RNAseqDataAnnotation.R --args /home/lornage/Bureau/Test_function /home/lornage/Bureau/ichierconvertitnames.txt Homo_sapiens 75 /home/lornage/Bureau/testttttt5.txt /home/lornage/Bureau/Script_R/Ensembl_Version_Host.txt /home/lornage/Bureau/Script_R/Ensemble_Specie_Dataset.txt
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