R package to find differentialy expressed genes

Question

[tulika.kakati]

Hello, I have three groups of samples, each with 10 values. Each group represent HIV-1 stage.I have 124 genes and I want to find differentially expressed genes across these three groups. I tried for two groups of samples using rowMeans(). Please help me .

sample of my query is given below:

    s1 s1 s1 s1 s1 s1 s1 s1 s1 s1 |   s2 s2 s2  s2 s2 s2  s2 s2 s2 s2 |  s3 s3 s3 s3  s3 s3 s3 s3 s3 s3
g1                                |                                                 |
g2                                |                                                 |
g3                                |                                                 |
g4                                |                                                 |
-                                 |                                                |
-                                 |                                                |
-                                 |                                                |
g124                              |                                                |

[Ram]

Your post is a question, not a tutorial. Please see How to Use Biostars, Part II: Post types, Deleting, (Un)Subscribing, Linking and Bookmarking for details on post types.

[tulika.kakati]

Thank you !! I am new to this forum.

[WouterDeCoster]

Please use ADD REPLY or ADD COMMENT when posting a reaction to a previous post, as such we keep this thread logically structured.

[WouterDeCoster]

How did you generate this data? qPCR? RNA-seq?

Answer 1

[Nicolas Rosewick]

Use limma, DESeq2 or edgeR. Search in biostars you'll find a lot of similar questions.

[WouterDeCoster]

He writes he has 124 genes so I'm not sure he has RNA-seq data...

[igor]

Good point, but it could be a simple species.

HIV-1 itself is only 10 genes: http://www.ncbi.nlm.nih.gov/genome/10319

[WouterDeCoster]

True, but I doubt whether the models of DESeq2 etc with regard to dispersion estimation still stand with such a limited number of genes.

[igor]

I've seen DESeq2 used for miRNA where you only have a few hundred "genes", so it's not entirely unreasonable.