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Good that it works; to check your top 20 tags I suggest you look at FPKM/RPKM or raw counts to make sure the 'direction' of regulation is correct. EdgeR gives "-logFC" for the first condition you provide IIRC. This can be confusing, and I still double check all results against FPKMs.
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Ok.. yah.. Thanks. I was making some silly input mistake in some earlier step too. That step, including your suggession make it work properly. But strangely, all 20 top tags are showing Downregulation in disease. That has made me a bit sceptical. I am doing double check now.
Thanks
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I think
v<- estimateGLMTrendedDisp(d , design)
should be
v<- estimateGLMTrendedDisp(z , design)
ie you have to run CommonDisp on 'd', and then run TrendedDisp on the output of that.
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edgeR issue:RNA seq
I am facing an error at the step Trended Dispersion, although no error during Common dispersion estimation.
rownames(design) <- colnames (d)
> z<- estimateGLMCommonDisp(d , design)
v<- estimateGLMTrendedDisp(d , design)
Error in t(y) + prior.count.scaled : non-conformable arrays
Please suggest what could be the reason, and what would be the way out.Tags: None
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The complexity of cancer is clearly demonstrated in the diverse ecosystem of the tumor microenvironment (TME). The TME is made up of numerous cell types and its development begins with the changes that happen during oncogenesis. “Genomic mutations, copy number changes, epigenetic alterations, and alternative gene expression occur to varying degrees within the affected tumor cells,” explained Andrea O’Hara, Ph.D., Strategic Technical Specialist at Azenta. “As...-
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