Question: comparisson of RNA-seq FPKMs across samples
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gravatar for lidia.mateo
2.7 years ago by
lidia.mateo • 0 wrote:

Dear BioStars community,

I am trying to "recycle" some RNA-seq data published as supplementary material of the publication "High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response" but I am not sure if I can really use it for my purpose.

I have a matrix of fpkm values per gene for 376 samples. For each gene in each sample, I would like to know whether the gene in this sample is highly expressed compared to the whole population (e.g obtain a Z-score for the expression of the gene in the sample given the expression of this gene in the whole population).

I have read that fpkm values depend on the sequencing depth of each sample and, therefore, cannot be directly compared across samples. Is there a way to somehow transform fpkm values into something that could be compared across samples?

I have never worked with RNA-seq data so any contribution will be more than welcome, even if you think it is a simple and basic comment or suggestion. I am comfortable programming with Python but I can also use R, perl or command line tools.

Many thanks in advance,

Lídia

rna-seq z-score fpkm • 967 views
ADD COMMENT • link • modified 2.7 years ago • written 2.7 years ago by lidia.mateo • 0
0
gravatar for Jennifer Hillman Jackson
2.7 years ago by
United States
Jennifer Hillman Jackson ♦ 25k wrote:

Hello

I do not personally know of a way to normalize pre-computed FPKM values from different experiments. I can see that you have also asked this question at the primary Biostars site and that will reach a larger audience. To avoid double topic posts, and because this question is not about Galaxy specifically, I think it is best to consider this question closed here and have others with feedback post there: https://www.biostars.org/p/180731/

Thanks, Jen, Galaxy team

ADD COMMENT • link written 2.7 years ago by Jennifer Hillman Jackson ♦ 25k
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gravatar for lidia.mateo
2.7 years ago by
lidia.mateo • 0 wrote:

Thank you! You are right, I thought I was posting at the primary Biostars site, sorry!

ADD COMMENT • link written 2.7 years ago by lidia.mateo • 0
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