Normalization of TCGA RNA-seq data (TPM) in R
Hi
I want to do normalization of raw TCGA RNA-seq expression data (TPM) in R. Can anyone share the suitable link for it?
Regards
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TPM is already normalized (a bit). Since the final application is important you'll have to tell us some more about what you aim to achieve after normalizing your data. Please be as informative as possible.
I have also adapted your title to make it more descriptive and added relevant tags to your question, as such experts can find it easier and provide you with appropriate answers. Take this into account when making new questions.
Thanks
I am having TPM values of different transcripts in normal and tumor patients. I have to apply Student t test to my data, and I think RNA seq data does not follow normal distribution, so I have to do quantile normalization before proceeding.
Please use
ADD COMMENTorADD REPLYto answer to previous reactions, as such this thread remains logically structured and easy to follow. I have now moved your reaction but as you can see it's not optimal. Adding an answer should only be used for providing a solution to the question asked.There are sophisticated packages for RNA-seq differential expression analysis, such as DESeq2 and edgeR. Just using a t-test and some normalisation will not suffice.
I use the DESeq2 to analysis differently expressed genes between tumor and normal tissue, the data which i select is Counts. however, i donn't know which kind of rna-seq data can i use to do survial analysis, or what normalized method can i use to normalize the FPKM data?
Don't use FPKM. Use vst or rlog transformed counts, which you can get from DESeq2.
thank you for reply. i will try this. i have another two problems. 1. can i used the rlog transformed data to do unsupervised clustering nanlysis, sunch as NMF. 2. when i use DESeq2 to do nanlysis of proteomics intensity data, i found DESeq2 seem to not handle 0, and it seems to think of 0 as NA, invalid class “DESeqDataSet” object: NA values are not allowed in the count matrix ,