Hello, generally speaking, when we are dealing with human tissues dataset (different hospitals, different days, etc.) we have to take into account the so-called batch effect. I have been practising with some useful tool such as SVA package but someone else like to cope with this issue in a slightly different way: either by doing a t-test on the whole dataset and designing a matrix.

I have always wondered why doing a t-test might control the batch effect, someone more expert than myself said that this is not so robust. It would be better to directly design a matrix...but it seems very hard for my beginner experience. But I guess it is something I have to learn because, for the kind of experiment I am doing (either on humans and mice) it is impossible to perform the experiment on the same day.

If someone could help me to understand:

1. if the design matrix is the best way to control batch effect,
2. how much we lose in term of reliability by doing a t-test (rather than a normal DESeq2 analysis)
3. if tools like SVA package can control the batch effect better than a design matrix written from scratch
4. if someone could also share the code from the DESeq2 package that allows to perform a t-test (either paired and unpaired) would really help me a lot since I was not able to find it.

Regards, Maria

DESeq2 is a package for analysis of count matrices for high throughput sequencing experiments. The t test isn’t really an alternative or an option within DESeq2.

Maybe read over the DESeq2 publication and then the beginners workflow and see if you have further specific questions.