Creating the correct model to account for paired-samples (patient-effect) help needed!
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22GL22 • 0
Last seen 6 weeks ago
United States

Hello there!

I'm hoping someone can help me set up an accurate model to fit my gene expression data (RNAseq) using limma. My study involves 10 patients. Two samples were collected from each patient (one cancer site and one uninvolved site), for a total of 20 samples.

patient condition
P01 uninvolved
P01 cancer
P02 uninvolved
P02 cancer
P03 uninvolved
P03 cancer
P04 uninvolved
P04 cancer
P05 uninvolved
P05 cancer
P06 uninvolved
P06 cancer
P07 uninvolved
P07 cancer
P08 uninvolved
P08 cancer
P09 uninvolved
P09 cancer
P10 uninvolved
P10 cancer

I want to account for the patient effect and ultimately compare genes up/down regulated between cancer and uninvolved groups. I've been looking through limma and edgeR's user manuals, as well as reading through the various posts here. If you have any guidance, please let me know.

Thanks in advance.Xx.

edgeR limma rnaseq • 137 views
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Last seen 6 hours ago
WEHI, Melbourne, Australia

In the limma User's Guide, Section 9.4.1 Paired Samples covers paired designs. In the edgeR User's Guide, it is Section 3.4.1.


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