readInterestResults {IntEREst} | R Documentation |
Reads one or multiple text file results generated by the interest
or interest.sequential
functions and builds an object of
SummarizedExperiment-class
class.
readInterestResults(resultFiles, sampleNames, sampleAnnotation, commonColumns, freqCol, scaledRetentionCol, scaleLength, scaleFragment, reScale=FALSE, geneIdCol, repeatsTableToFilter=c())
resultFiles |
Vector of character strings which includes the path to the tab-separated files
resulted by the |
sampleNames |
Vector of character strings which includes the name of the samples. It should
be the same size as the |
sampleAnnotation |
Data frame with the same row number as the size of |
commonColumns |
Columns in the result file which include intron/exon annotations and are common
across all files defined in |
freqCol |
Column in the result file which include the read counts for introns/exons. |
scaledRetentionCol |
Column in the result file which include the scaled retention values for introns/exons. |
scaleLength |
Logical value, indicating whether the intron/exon retention levels are scaled
to the length of the introns/exons. If |
scaleFragment |
Logical value, indicating whether the intron/exon retention levels are scaled
to the fragments mapped to the genes. If |
reScale |
Logical value, indicating whether the scaled retention levels would be
rescalculated when reading the data. By default it does not calculate and
trusts the user to set the |
geneIdCol |
The number or name of the column in |
repeatsTableToFilter |
A data.frame table with similar stucture to the
|
An object of calss
SummarizedExperiment-class
.
Ali Oghabian
geneId<- paste("gene", c(rep(1,7), rep(2,7), rep(3,7), rep(4,7)), sep="_") readCnt1<- sample(1:100, 28) readCnt2<- sample(1:100, 28) readCnt3<- sample(1:100, 28) readCnt4<- sample(1:100, 28) fpkm1<- readCnt1/(tapply(readCnt1, geneId, sum))[geneId] fpkm2<- readCnt2/(tapply(readCnt2, geneId, sum))[geneId] fpkm3<- readCnt3/(tapply(readCnt3, geneId, sum))[geneId] fpkm4<- readCnt4/(tapply(readCnt4, geneId, sum))[geneId] #Create tmp director tmpDir=file.path(tempdir(),"InterestResult") dir.create(tmpDir) # Build text files similar to files resulted by interest dfTmp=data.frame( int_ex=rep(c(rep(c("exon","intron"),3),"exon"),4), int_ex_num= rep(c(1,1,2,2,3,3,4),4), int_type=rep(c(NA,"U2",NA,"U12",NA,"U2",NA),4), strand=rep("*",28), gene_id= geneId, sam1_readCnt=readCnt1, sam2_readCnt=readCnt2, sam3_readCnt=readCnt3, sam4_readCnt=readCnt4, sam1_fpkm=fpkm1, sam2_fpkm=fpkm2, sam3_fpkm=fpkm3, sam4_fpkm=fpkm4 ) writeDf<-function(df, file){ write.table(df, file, col.names=TRUE, row.names=FALSE, quote=FALSE, sep='\t') } writeDf(dfTmp[, c(1:5,6,10)], paste(tmpDir, "df1.tsv", sep="/")) writeDf(dfTmp[, c(1:5,7,11)], paste(tmpDir, "df2.tsv", sep="/")) writeDf(dfTmp[, c(1:5,8,12)], paste(tmpDir, "df3.tsv", sep="/")) writeDf(dfTmp[, c(1:5,9,13)], paste(tmpDir, "df4.tsv", sep="/")) # Build object from generated text file results testObj<-readInterestResults( resultFiles=paste(tmpDir, c("df1.tsv", "df2.tsv", "df3.tsv", "df4.tsv"), sep="/"), sampleNames=c("sam1","sam2","sam3","sam4"), sampleAnnotation= data.frame( gender=c("M","M","F","F"), health=c("healthy","unhealthy","healthy","unhealthy")), commonColumns=1:5, freqCol=6, scaledRetentionCol=7, scaleLength=FALSE, scaleFragment=TRUE, reScale=FALSE) #View object testObj