among RPKM, DESeq, TMM and so on...
Which one do you prefer and why??!
Which one do you prefer and why??!
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Generally DESeq'2 method or TMM, depending on whether I'm using DESeq2 or edgeR (why? Because they're done by default and work fine). RPKM should never be used (there are many papers on this). Quantile normalization is also popular, though you wouldn't normally use that on count data (though you could use it in conjunction with limma). Generally you get the same results regardless of the method (except RPKM, which you should never use as a normalization method). -
Thank you, Devon Ryan. I usually use DESeq but I just saw a company provided their client RNA-seq data normalized by RPKM.Comment
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Please can someone solve this assignment by using Gauss elimination method (please write the procedure step by step so I could understand it). Thank you very much.
Update: if it is easy why wouldn't you do it?Comment
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@ithersam: I hope you realize that we have absolutely no clue what you're talking about. BTW, you should do your own assignments.Comment
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Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing... -
The immune system’s power comes from its genetic diversity, allowing myriad threats to be neutralized through first recognizing foreign antigens. That diversity is also what makes the immune system so difficult to study. Recent advances in sequencing technology and computational biology, however, are giving researchers new tools to understand immune responses and immune-related diseases in greater detail.
This convergence of genetics, immunology, and computation...09-01-2026, 05:41 AM
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