I am having a RNA seq analysis file in the following format with all the 4 samples are in replicates (test file). Now if I want to do differential analysis how should I proceed? Is there any tool or do I need to use a custom script?
Id S1.1 RPKM S1.2 RPKM S2.1 RPKM S2.2 RPKM S3.1 RPKM S3.2 RPKM S4.1 RPKM S4.2 RPKM
G1 37.6 45.9 126.9 40.8 25.1 35.1 142.1 163.3
G2 57.1 71.5 444.5 50.8 5.8 4.7 14.4 9.0
G3 92.0 96.8 110.0 302.9 5.9 5.2 196.3 155.3
G4 94.0 84.7 7.1 46.8 18.1 30.9 10.3 3.3
G5 15.1 10.5 78.7 3.7 164.2 41.6 7.4 1.3
G6 11.2 15.1 50.9 47.4 3.3 1.2 7.4 2.0
G7 13.2 18.6 12.7 46.8 .3 7.1 8.1 2.6
G8 51.6 71.4 9.9 19.2 44.3 34.2 3,059.4 3,671.7
G9 1,206.3 779.2 5.2 10.7 1.4 10.3 321.8 312.7
G10 12.2 16.5 19.4 7.3 6.2 10.4 104.0 120.6
G11 250.4 269.3 76.4 25.4 1.7 7.0 24.7 24.7
G12 59.5 83.3 .0 27.0 4.7 12.9 24.0 21.4
G13 19.4 22.0 71.5 .0 5.8 18.3 21.8 27.3
G14 363.3 100.4 33.1 27.0 45.3 22.1 98.0 290.1
G15 7.4 8.5 4.1 43.7 2.8 3.6 1.9 2.2
G16 37.5 34.3 2.1 4.4 32.6 20.3 3.2 2.6
Go for R (and RStudio) and use a package such as EdgeR, DESeq2, etc.
You got already the hardest part: to get a table with genes names and counts
By reading the package vignettes, you have a easy way of analyzing your data. Don't be scared.
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written
by
Antonio R. Franco
EdgeR, DESeq2, etc. aren't intended to be used with RPKMs, so they may or may not yield sensible results when given them. A better strategy would be to see if more useful counts (raw or estimated would be preferred) can be obtained.
You are right. I did not notice that numbers were RPKM
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