I'm dealing with RNA seq data and obtained FPKM value using cufflinks for treated and control samples. Do i want to normalize these value to obtain p-value or it is sufficient to find DE genes?. If i want to calculate p value using this FPKM. what would be the best test to go with this? How to get the P value?. So far I have used fold change values and created Venn diagrams to show transcripts between each condition. I need to find DE genes. I am new to this field and So anyone please give some solution for me to move step forward.
Take a look at this link, it'll tell you all you need
http://www.bioconductor.org/help/workflows/rnaseqGene/
Hi Ranjith,
For analyzing DE of genes, I suggest you to use R packages such as edgeR or DEseq2. These package use read counts mapped to your gene (output of htseq-count for example) and they will allow you to get rpkm values as well as list of significantly DE genes.
Best,
Jonathan
If you used tuxedo suite (like tophat, cufflink, etc), you can use cuffdiff to find DE genes.
You can get the info. from the following link.
http://cole-trapnell-lab.github.io/cufflinks/cuffdiff/
Best,
Daekwan
You can use DeSeq package to calculate the p-values. This program takes read count of different samples, against the common reference, as input.
I completely agree with Carlo, you want to use DEseq/edgeR/etc to analyze DE genes and not FPKM values.
I have RNA seq data as DEG, how to get p value for these data set. Which require to make Volcano plot ?