mkatari-bioinformatics-august-2013-deseq
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| mkatari-bioinformatics-august-2013-deseq [2015/06/17 06:15] – mkatari | mkatari-bioinformatics-august-2013-deseq [2015/08/21 14:13] (current) – mkatari | ||
|---|---|---|---|
| Line 21: | Line 21: | ||
| First we will load the count data file. | First we will load the count data file. | ||
| < | < | ||
| - | counts = read.table(pathToCountsData, header=T, row.names=1) | + | counts = read.table(" |
| </ | </ | ||
| Then we will load the experimental design. An example is provided [[https:// | Then we will load the experimental design. An example is provided [[https:// | ||
| < | < | ||
| - | expdesign = read.table(pathToExpDesign) | + | expdesign = read.table(" |
| </ | </ | ||
| Line 53: | Line 53: | ||
| An important part of DESeq is to estimate dispersion. This is simply a form of variance for the genes. | An important part of DESeq is to estimate dispersion. This is simply a form of variance for the genes. | ||
| < | < | ||
| + | # if you have replicates do the following: | ||
| cds = estimateDispersions( cds ) | cds = estimateDispersions( cds ) | ||
| + | ### HOWEVER, If you have NO replicates, then try this | ||
| + | cds = estimateDispersions( cds, method=" | ||
| </ | </ | ||
| To visualize the disperson graph | To visualize the disperson graph | ||
| < | < | ||
| - | dispersionFile = paste(pathToOutputDir, | + | dispersionFile = " |
| pdf(dispersionFile) | pdf(dispersionFile) | ||
| plotDispEsts( cds ) | plotDispEsts( cds ) | ||
| Line 77: | Line 80: | ||
| < | < | ||
| - | maFile = paste(pathToOutputDir, | + | maFile = " |
| pdf(maFile) | pdf(maFile) | ||
| plotMA(res) | plotMA(res) | ||
| Line 85: | Line 88: | ||
| #To get the genes that have FDR of 10% and save it in the output directory. | #To get the genes that have FDR of 10% and save it in the output directory. | ||
| < | < | ||
| - | resSig | + | resSigind |
| + | resSigrep = res[ which(res$padj < 0.1 & res$log2FoldChange < -1), ] | ||
| - | outfile | + | indoutfile |
| + | repoutfile | ||
| - | write.table(resSig, | + | write.table(resSigind, |
| - | | + | |
| + | sep=" | ||
| + | col.names=T, | ||
| + | row.names=F, | ||
| + | quote=F) | ||
| + | |||
| + | write.table(resSigrep, | ||
| + | repoutfile, | ||
| sep=" | sep=" | ||
| col.names=T, | col.names=T, | ||
mkatari-bioinformatics-august-2013-deseq.1434521738.txt.gz · Last modified: by mkatari