hi Ming,

We do not recommend using rounded estimated values of read counts with
DESeq2 (although I found an email from myself to the list one year ago
contradicting this in the case that someone had no access to the raw
data)​. Counts of reads which are proportionally assigned to genes and then
rounded can be a bad fit for distributions like the Negative Binomial (and
Poisson). For example, this procedure could generate values arising from a
distribution that has variance less than the mean. As a rule, and to help
avoid erroneous results, users should produce a matrix containing integer
counts of reads uniquely aligned to features.

Mike




On Wed, Jan 29, 2014 at 11:16 AM, Ming Yi <yi02@hotmail.com> wrote:

>
> Hi, Dear Michael:
>
>
>
> Sorry to directly jump in a quick question, since I saw you respond to
> some DESeq questions yesterday and I know you are the author of DESeq2
> package.
>
>
>
> I run into some RNAseq data issue with edgeR package (see my post in BioC
> yesterday), since the data I used are not integer counts of genes, but RSEM
> processed raw_count from TCGA RNA-seq data, in fact, are not integers,
> although TCGA named it as raw_count (I showed some piece of such a file
> from TCGA as below).
>
>
>
> file name:
> "unc.edu.1b4bb160-191b-4796-8759-339b11fe386d.1096727.rsem.genes.results"
>
> its content looks below:
>
>      gene_id raw_count scaled_estimate         transcript_id
>
> 1 ?|100130426      0.00    0.000000e+00            uc011lsn.1
>
> 2 ?|100133144      4.67    1.794813e-07 uc010unu.1,uc010uoa.1
>
> 3 ?|100134869     15.33    4.271899e-07 uc002bgz.2,uc002bic.2
>
> 4     ?|10357    218.79    1.933490e-05            uc010zzl.1
>
> 5     ?|10431   1255.00    5.033411e-05 uc001jiu.2,uc010qhg.1
>
> 6    ?|136542      0.00    0.000000e+00            uc011krn.1
>
>
>
> I used the raw_count of this file for edgeR analysis and run into some
> warning messages which indicating potential issues, and had been pointed
> out by Dr. Smyth as you may have seen in my post yesterday.
>
>
>
> Reading the user guide from both DESeq and DESeq2, both packages mentioned
> the input was expected to be count data in a form of a matrix of integer
> values, not even (rounded) normalized counts, which would lead to
> nonsensical results.
>
>
>
> The TCGA data above apparently are not true raw counts but some kind of
> RSEM processed raw_counts. Although both RSEM authors and TCGA data staff
> all suggested the raw_count can be used for edgeR and DESeq (or DESeq2)
> analysis, because of the issues I run into in edgeR. I wonder what would be
> your opinion on this data for analysis in DESeq2?
>
>
>
> Any advice would be appreciated very much!
>
>
>
> Thanks and best
>
>
>
> Ming Yi
>
> NIH
>
> Maryland,USA
>



On Wed, Jan 29, 2014 at 11:16 AM, Ming Yi <yi02@hotmail.com> wrote:

>
> Hi, Dear Michael:
>
>
>
> Sorry to directly jump in a quick question, since I saw you respond to
> some DESeq questions yesterday and I know you are the author of DESeq2
> package.
>
>
>
> I run into some RNAseq data issue with edgeR package (see my post in BioC
> yesterday), since the data I used are not integer counts of genes, but RSEM
> processed raw_count from TCGA RNA-seq data, in fact, are not integers,
> although TCGA named it as raw_count (I showed some piece of such a file
> from TCGA as below).
>
>
>
> file name:
> "unc.edu.1b4bb160-191b-4796-8759-339b11fe386d.1096727.rsem.genes.results"
>
> its content looks below:
>
>      gene_id raw_count scaled_estimate         transcript_id
>
> 1 ?|100130426      0.00    0.000000e+00            uc011lsn.1
>
> 2 ?|100133144      4.67    1.794813e-07 uc010unu.1,uc010uoa.1
>
> 3 ?|100134869     15.33    4.271899e-07 uc002bgz.2,uc002bic.2
>
> 4     ?|10357    218.79    1.933490e-05            uc010zzl.1
>
> 5     ?|10431   1255.00    5.033411e-05 uc001jiu.2,uc010qhg.1
>
> 6    ?|136542      0.00    0.000000e+00            uc011krn.1
>
>
>
> I used the raw_count of this file for edgeR analysis and run into some
> warning messages which indicating potential issues, and had been pointed
> out by Dr. Smyth as you may have seen in my post yesterday.
>
>
>
> Reading the user guide from both DESeq and DESeq2, both packages mentioned
> the input was expected to be count data in a form of a matrix of integer
> values, not even (rounded) normalized counts, which would lead to
> nonsensical results.
>
>
>
> The TCGA data above apparently are not true raw counts but some kind of
> RSEM processed raw_counts. Although both RSEM authors and TCGA data staff
> all suggested the raw_count can be used for edgeR and DESeq (or DESeq2)
> analysis, because of the issues I run into in edgeR. I wonder what would be
> your opinion on this data for analysis in DESeq2?
>
>
>
> Any advice would be appreciated very much!
>
>
>
> Thanks and best
>
>
>
> Ming Yi
>
> NIH
>
> Maryland,USA
>

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