Entering edit mode
3.8 years ago
anasjamshed
▴
120
I want to do methodology of the following paper first I downloaded microarray data GSE75693 then I need to identify DEGs in R. There are 55 thousand genes in 79 samples through which I need to find DEGs that were selected based on the threshold P < 0.01 and fold change >2.0
https://www.nature.com/articles/s41598-018-23492-2
Microarray data of BKVN and stable kidney transplantation patients were compared by the limma package by the linear model, the contrast model and the DEG selection. Now I want to do it in R by myself
I'll be honest. It's not a really good paper. Analyzing a single public dataset and doing mediocre heatmaps & downstream pathway analysis shouldn't get a paper. Many hypotheses were tested but it's not clear in the text where any p-value correction was performed. The supplementary data is lacking -- if they're not going to release reproducible code, at least report the entire analyses -- not just the results that passed their threshold. Further, there are typos and inaccurate descriptions. Not sure what value this paper adds beyond the unsurprising result that "certain genes change between conditions".
The public dataset itself is useful to analyze. Not sure what your question is -- you want to do it in R by yourself; no one is stopping you from doing so. Have you tried reading the limma tutorials? Have you figured out how to download the data and read it into an R data frame or matrix? What have you tried?
yes, sir, I tried but unable to calculate DEGs from 55000 genes
Why? Can you post what you've tried and what errors you're getting?
Saying you can't do something is not a good way to ask a question or get help.
I read data from the matrix file but after that, I am unable to perform any function.