Dear Evan,

I have a similar question for a long time. For different platform (rtPCR
vs. high-throughput array/sequencing), the number of genes vs. the number
of samples, which one is a more important issue for ComBat, for example,
here are two data I have:

1. a rtPCR data with 100 genes, but 2000 samples from 30 batches
2. a RNA-seq data with >25,000 genes, but only 14 samples from 2 different
batches, is ComBat an optimal tool to correct batch effect comparing to
removeBatchEffect() in edgeR?

Many thanks,
Shirley


On Thu, May 22, 2014 at 7:07 AM, Johnson, William Evan <wej@bu.edu> wrote:

> Hi Giuliano,
>
> ComBat should work fine, just be cautious about outlier genes and samples,
> because these could influence the results. Outliers are usually less of a
> problem in microarray studies because there are so many genes, but in your
> case outliers could have more influence. To check this, look for
> abnormalities in the heatmap and also look for gross violations from
> normality in the prior plots generated by ComBat.
>
> Thanks!
>
> Evan
>
>
> On May 22, 2014, at 4:33 AM, Giuliano Stirparo <giulianostirparo@gmail.com>
> wrote:
>
> >  Dear All
> > I am trying to use combat to perform batch correction of RT-PCR data. In
> particular I have around 40 genes and 59 samples.
> > The samples are divided in two categories (resistant on a particular
> treatment and sensitive) and they come from different batch (6 samples + 19
> samples + 24 samples).
> > To perform batch correction I used the default parameter. I was
> wondering if it is possible use ComBat for this kind of analysis or if I
> have to try with different tools.
> > If you need more details please do not hesitate to contact me.
> >
> > Best
> >
> > Giuliano Stirparo
>
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