Thanks Sean for your response.

Regards,
Nirmala

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From: Davis, Sean (NCI) On Behalf Of Davis, Sean (NIH/NCI) [E]
Sent: Friday, December 14, 2012 4:45 PM
To: Akula, Nirmala (NIH/NIMH) [C]
Cc: bioconductor@r-project.org
Subject: Re: [BioC] filtering before using DESeq


On Fri, Dec 14, 2012 at 2:42 PM, Akula, Nirmala (NIH/NIMH) [C] <akulan@mail.nih.gov<mailto:akulan@mail.nih.gov>> wrote:
Hi,

We counted the reads in our RNA-seq data using HT-seq and removed any isoforms that have <5 reads/sample. We then used DESeq for differential expression analysis.

Here's an example of a transcript that has the following read counts:


GeneA_cases counts:
85.78942

19.11753

1471.813

61.71464


GeneA_control counts:

2088.722

2681.746

2413.892

1628.187



DESeq p-value for GeneA is 10-4. Do we have to filter out transcripts (that have high variance between samples as shown in the above example) before giving the data to DESeq or will DESeq take this into account while calculating the normalization?

Hi, Nirmala.

If you mean filtering out transcripts that show one or more outliers within a given group, then you should ABSOLUTELY NOT do that as this will bias your statistical results.  If you mean filtering based on overall variance (across groups) to find highly-variable transcripts, that is a different story and is acceptable.

Sean


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