Deleted:More significant candidates and more skewed to the left why using more samples, why?
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W. Gi • 0
@w-gi-14740
Last seen 2.1 years ago
Germany

Dear colleagues,

Please help me!

I was using DESeq2 to analyze gene expression from a batch of IPSCs and have observed some results that I can't explain.

The study design was that there were 3 iPSCs derived from skin biopsy from patient A with Mutation X, and other 3 iPSCs from patient B with Mutation X, therefore in total 6 iPSCs, supposedly all with mutation X. Also, there were 7 iPSCs derived from healthy individuals (in total 5 individuals) as controls.

First, I ran the DESeq2 on the cohort the 3 iPSCs derived from patient A with mutation X and all control iPSC cells and got the following graph: enter image description here https://photos.app.goo.gl/2VpiBRhbDcw1Zy468

Second, I ran the DESeq2 on the cohort the 3 iPSCs derived from patient B with mutation X and all control iPSC cells and got the following graph: enter image description here https://photos.app.goo.gl/f9YD6CQquxWwQRkU7

At last, I ran the DESeq2 on the cohort the 6 iPSCs derived from patient A and patient B with mutation X and all control iPSC cells and got the following graph: enter image description here https://photos.app.goo.gl/FdJbm9ReymU4Twrr8

There are two questions:

1) Why does the distribution of the volcano plot skew so bizarrely to the left when I analyzed all 16 samples together, which was not the case when I analyzed only samples from a single patients versus controls? 2) Why are there much more statistically significant candidates when I analyzed all 16 samples together, which was not the case when I analyzed only samples from a single patients versus controls?

Your answers and suggestions would be highly helpful for me. Thank you very much for your time and patience.

Best regards, Weng-Tein Gi

deseq2 • 838 views
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