Question

DESeq Question

0

Entering edit mode

OD ▴ 40

@od-5180

Last seen 9.4 years ago

United States

Hello All, I am trying to use DESeq, a sample of my data looks like below (X.1 & X.2 are replicates, Y1 & Y2 are replicates). *GeneNo X.1 X.2 Y.1 Y.2* gene00001 4 3 3 1 gene00002 17 45 39 30 gene00003 25 40 29 24 gene00004 8 8 9 3 gene00009 1 0 0 0 gene00011 1 2 4 2 gene00012 0 0 0 0 gene00014 17 7 8 21 I used the following commands to find the differentially expressed genes. I have two questions, 1. Are the following commands correct ? or am i missing something? 2. How can i determine which genes are differentially expressed? induced? suppressed? unchanged? library( "DESeq" ) exampleFile = system.file( "extra/X_Y_Reads.txt", package="DESeq" ) countsTable <- read.delim( exampleFile, header=TRUE, stringsAsFactors=TRUE ) rownames( countsTable ) <- countsTable$gene countsTable <- countsTable[ , -1 ] conds <- c( "X","X","Y","Y") cds <- newCountDataSet( countsTable, conds ) libsizes <- clibsizes <- c(X.1=18143070, X.2=13544150, Y.1=17853990, Y.2=15038501) sizeFactors(cds) <- libsizes[-1] cds <- estimateSizeFactors( cds ) sizeFactors( cds ) cds <- estimateDispersions( cds ) res <- nbinomTest( cds, "X", "Y" ) plot(res$baseMean,res$log2FoldChange,log="x", pch=20, cex=.1,col = ifelse( res$padj < .001, "red", "black" ) ) resSig <- res[ res$padj < .001, ] head( resSig[ order(resSig$pval), ] ) write.table(res,"C:\\Users\\OMD\\Desktop\\XY_DEG.txt") -- Thank you, [[alternative HTML version deleted]]

DESeq DESeq • 1.3k views

ADD COMMENT • link updated 12.7 years ago by Simon Anders ★ 3.8k • written 12.7 years ago by OD ▴ 40

score 0 · Answer 1 · 2012-03-21

0

Entering edit mode

Simon Anders ★ 3.8k

@simon-anders-3855

Last seen 4.3 years ago

Zentrum für Molekularbiologie, Universi…

Hi On 03/21/2012 12:26 AM, Omar Darwish wrote: > I used the following commands to find the differentially expressed genes. > I have two questions, > > 1. Are the following commands correct ? or am i missing something? Yes, except for two oddities: > libsizes<- clibsizes<- c(X.1=18143070, X.2=13544150, Y.1=17853990, > Y.2=15038501) > sizeFactors(cds)<- libsizes[-1] > cds<- estimateSizeFactors( cds ) Why do you set the size factors manually, and the use 'estimateSizefactors' to overwrite this information? The first two commands are gratuitous (and don't even work becaus of the "[-1]"). Omit them. > resSig<- res[ res$padj< .001, ] Do your really want an FDR of only 0.1%? This is extremely stringent. Do you have any reason for this unusual choice? > 2. How can i determine which genes are differentially expressed? > induced? suppressed? unchanged? Those with and adjusted p value (column "padj") below your chosen FDR threshold are significant, and the column "log2FoldChange" tells you the log2 fold change and hence whether they are up- or downregulated. Simon

ADD COMMENT • link 12.7 years ago Simon Anders ★ 3.8k

0

Entering edit mode

Thanks Simon, Well, so i omitted the two commands you mentioned, my commands now: library( "DESeq" ) exampleFile = system.file( "extra/X_Y_Reads.txt", package="DESeq" ) countsTable <- read.delim( exampleFile, header=TRUE, stringsAsFactors=TRUE ) rownames( countsTable ) <- countsTable$gene countsTable <- countsTable[ , -1 ] conds <- c( "X","X","Y","Y") cds <- newCountDataSet( countsTable, conds ) cds <- estimateSizeFactors( cds ) sizeFactors( cds ) cds <- estimateDispersions( cds ) res <- nbinomTest( cds, "X", "Y" ) plot(res$baseMean,res$log2FoldChange,log="x", pch=20, cex=.1,col = ifelse( res$padj < .001, "red", "black" ) ) resSig <- res[ res$padj < .001, ] head( resSig[ order(resSig$pval), ] ) write.table(res,"C:\\Users\\OMD\\Desktop\\XY_DEG.txt") Regarding the FDR, honestly I'm not really sure what is the best cut off value to use, I picked 0.001 based on what I saw in one of the examples published in the DESeq paper! Any recommendations! I have one more question, in the output file i can see only integer ids (1,2,3,4 ... etc) instead of the (gene0001, gene0023 ... etc ), I am not sure if these integers match the gene numbers as in my input Regards, On Wed, Mar 21, 2012 at 10:18 AM, Simon Anders <anders@embl.de> wrote: > Hi > > > On 03/21/2012 12:26 AM, Omar Darwish wrote: > >> I used the following commands to find the differentially expressed genes. >> I have two questions, >> >> 1. Are the following commands correct ? or am i missing something? >> > > Yes, except for two oddities: > > > > libsizes<- clibsizes<- c(X.1=18143070, X.2=13544150, Y.1=17853990, > > Y.2=15038501) > > sizeFactors(cds)<- libsizes[-1] > > cds<- estimateSizeFactors( cds ) > > Why do you set the size factors manually, and the use > 'estimateSizefactors' to overwrite this information? The first two commands > are gratuitous (and don't even work becaus of the "[-1]"). Omit them. > > > > resSig<- res[ res$padj< .001, ] > > Do your really want an FDR of only 0.1%? This is extremely stringent. Do > you have any reason for this unusual choice? > > 2. How can i determine which genes are differentially expressed? >> induced? suppressed? unchanged? >> > > Those with and adjusted p value (column "padj") below your chosen FDR > threshold are significant, and the column "log2FoldChange" tells you the > log2 fold change and hence whether they are up- or downregulated. > > Simon > > ______________________________**_________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/**listinfo/bioconductor<https: stat.et="" hz.ch="" mailman="" listinfo="" bioconductor=""> > Search the archives: http://news.gmane.org/gmane.** > science.biology.informatics.**conductor<http: news.gmane.org="" gmane.="" science.biology.informatics.conductor=""> > -- Regards, Omar [[alternative HTML version deleted]]

ADD REPLY • link 12.7 years ago OD ▴ 40