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Old 04-04-2010, 09:52 PM   #14
Location: Ames, IA

Join Date: Nov 2008
Posts: 57
Default Re: Bowtie-Tophat SAM output for read count assembly

Originally Posted by Simon Anders View Post
If you want to test for differential expression, it is a good idea to stay on the level of raw, integer counts, and not use RPKM or related data that is normalized by transcript length. This is because significance depends on the number of actual reads that you count. If you have low count you need to see a high fold-change to call significance.

See this thread for more details: (especially from post #6 onwards)

If you work with count data, your testing procedure needs to be aware of the ratios of sequencing depths of the libraries. This functionality is offered by several tools, namely edgeR, DESeq, and cuffdiff. I recommend DESeq, of course, as it is our work. ;-)
Hi Simon
I have used Bowtie, Tophat and Cufflinks to align and assemble maize RNA-seq data. Cufflinks reports FPKM values which our statistics collaborator is not able to use as it has already been normalized. Can I use the Bowtie, Tophat generated 'SAM' output in some other program to assemble the data in way that I will have absolute read counts per gene or transcript? If so what other programs would you recommend?

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