[BioC] Combing Effects (t-stats) from experiment with common reference design?

Atul atulkakrana at outlook.com
Fri Aug 29 03:21:03 CEST 2014

Hi Ryan,

Thanks for taking out time to reply to my question. I have samples from 
two tissues - Heart (20 different developmental stages) and Control 
(rest of the body, single fused sample from multiple time points). I 
performed 'limma' analysis (GLM approach) to identify up-regulated genes 
for each of the Heart stages (n=20).

Ex comparisons:
Heart Stage-1 vs. Control-X
Heart Stage-2 vs. Control-X
Heart Stage-20 vs. Control-X

Now I would like to rank genes on the basis of their enrichment in heart 
across all stages. So that a gene which is highly enriched in heart 
should rank high (on top) and genes which are not enriched in heart 
should rank low (at bottom). Is there any way to combine 't-stats' for 
each stage to a single metric? Or any other method rank genes that are 
enriched in Heart across all stages?

Actually I do have F-statistic. But I think that F-stat is high for gene 
which shows variable enrichment i..e gene which is not enriched in 5 
stages but enriched in 15 stages will have better F-stat reather than a 
gene with enrichment in all 20 stages. Therefore 'F-stat' doesn't seem 
to be the correct indication of enrichment level across all stages. I 
might be wrong, please correct me if that the case.



On 08/28/2014 06:09 PM, Ryan C. Thompson wrote:
> Hi Atul,
> Typically if you are testing multiple contrasts simultaneously, you 
> would use an ANOVA test that would five you an F statistics (and 
> corresponding p-value). But it's not exactly clear if that's what 
> you're asking for, Can you explain in more detail exactly which 
> hypothesis you are trying to test? Ar you trying to test whether any 
> of the Stages is different from the control, or are you trying to test 
> whether genes are changing between all Stages?
> -Ryan
> On Thu 28 Aug 2014 12:52:47 PM PDT, Atul wrote:
>> Hi All,
>> I was wondering whether there is any approach to combine 't-stat' from
>> different comparisons but using same control. These are my contrasts:
>> Stage1 vs ControlX
>> Stage2 vs ControlX
>> Stage3 vs. ControlX
>> .........
>> Stage 20 vs. ControlX
>> Here the control is same i.e. same sample for all contrasts. From
>> 'limma' analysis I have Fold change, t-stats and p-values for each gene.
>> Now, is it possible to combine 't-stats' from all different stages to
>> single value? Or compute a single combined value for all the contrasts.
>> So, that this single metric could be used to rank genes across all time
>> points. Is there any package available to do so? I can find methods to
>> combine p-values but not the 't-stat'.
>> Thanks
>> AK
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