[BioC] RNASeq: normalization issues

[ywchen at jimmy.harvard.edu]

Hi Wei,

Could you elaborate on how to appropriately do gene-length-adjusted
quantile normalization in edgeR? The "quantile normalization" option in
calcNormFactors function does not seem to take into account the gene
length.

Thanks.
Yiwen
> Hi João:
>
> 	Maybe you can try different normalization methods for your data to see
> which one looks better. How to best normalize RNA-seq data is still of
> much debate at this stage.
>
> 	You can try scaling methods like TMM, RPKM, or 75th percentile, which as
> you said normalize data within samples. Or you can try quantile
> between-sample normalization (read counts should be adjusted by gene
> length first), which performs normalization across samples. You can try
> all these in edgeR package.
>
> 	From my experience, I actually found the quantile method performed better
> for my RNA-seq data. I used general linear model and likelihood ratio
> test in edgeR in my analysis.
>
> 	Hope this helps.
>
> Cheers,
> Wei
>
> On Apr 28, 2011, at 7:36 PM, João Moura wrote:
>
>> Dear all,
>>
>>
>> Until now I was doing RNAseq DE analysis and to do that I understand
>> that
>> normalization issues only matter inside samples, because one can assume
>> the
>> length/content biases will cancel out when comparing same genes in
>> different
>> samples.
>> Although, I'm now trying to compare correlation of different genes and
>> so,
>> this biases should be taken into account - for this is there any better
>> method than RPKM?
>>
>> My main doubt is if I should also take into acount the biases inside
>> samples
>> and to do that is there any better approach then TMM by Robinson and
>> Oshlack
>> [2010]?
>>
>> Thank you all,
>> --
>> João Moura
>>
>> 	[[alternative HTML version deleted]]
>>
>> _______________________________________________
>> Bioconductor mailing list
>> Bioconductor at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
>
> ______________________________________________________________________
> The information in this email is confidential and intend...{{dropped:6}}
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>