Hi, Everyone, I am a real beginner in bioinformatics. I want to calculate differential expression profile of my TCGA data-mRNAseq(by using 5 normal, 5 tumor samples).However,to calculate this, I have RPKM values which requires non-parametric methods. Actually, I will upload this data to IPA(Ingenuity Pathway Analysis) tool to predict pathways,targets(for miRseq data from TCGA), upstream/downstream regulators. When I watch IPA tutorial, I realized that to predict all these from RNA-seq data, I need LogfoldChange value,dependent p-value and False DiscoveryRate. Unfortunately, I have not that much background how to deal with these calculations,how to calculate all of these from my RPKM valued TCGA data. Can anyone help me? Thanks a lot!
Question: TCGA data(RPKM) differential gene expression
2.3 years ago by
realnewbie • 10
realnewbie • 10 wrote:
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