removing batch effects from large number of data sets

Question

[nazaninhoseinkhan]

Dear all,

I want to find differential expressed genes between cancer and adjacent normal tissues from large number of microarray data sets (52).

Each data set consists of large number of samples of affymetrix or agilent platforms.

I don't have access to server at the moment and I want to know if I can get the list of DEGs for each sample separately and then obtain the overlap between these 52 data sets.

I know removing batch effects is of great significance before integrating the results of these studies, but I want to know how much not performing it affect the results.

I will appreciate any comments

Regards
Nazanin

Answer 1

[BioinfGuru]

First step would be to PCA the 52 samples to see if they separate by potential causes of batch effects e.g. by platform or lab.

Take a look at the following posts to get started:

1) What is the simple way to remove known batch effect from RNA-seq data ?

2) Correct for batch-effects which are not visible in pca-plot of raw-data (RNA-Seq)

3) How To Define Batch And Covariate To Remove Batch Effects With Combat.R

4) All biostars links on batch effects

5) Finally, highly recommended paper on batch effects