RNA seq differential analysis

Question

[peris]

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

Answer 1

[Antonio R. Franco]

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.

[Devon Ryan]

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.

[Antonio R. Franco]

You are right. I did not notice that numbers were RPKM

[peris]

Thanks you.