I am a complete beginner at 'R', so bear with me. Currently, I have an RNA seq data set that identifies two clusters (High exp samples and Low exp samples) based on a gene set. I now want to explore the differential expression of the remaining 20k genes between these two clusters. My advisor has told me to use limma, and I found a pretty useful link : RNA-Seq analysis is easy as 1-2-3. My approach was to conduct the limma analysis separately for the two clusters. Half way through my attempt I began to question if that was right, as the article kept mentioning DGE compares between conditions..
My question is: How do I prepare my RNA-Seq data. Currently, it is framed as Rows: Samples Columns: Genes How do I factor in the two clusters in this data frame, to use for DGE? If there is a complete dumbed down version, please do tell. Any help is appreciated.
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simran.ven •
The components of any expression study are usually:
The order of the metadata rows should match that of the columns of the expression matrix.
You can compare anything that you want in a differential expression analysis. Condition is a term that just happens to be used a lot in tutorials.
When I was a beginner in Bioinformatics, I went through those types of tutorials on my own, making my own comments in my code. Once completed, it then served as a 'prototype' that I could then apply to my own data. I suggest that you take this approach. Take the time to go through the tutorial, and using the data that they use in the tutorial itself.
Kevin
Thank you for being kind enough to explain the crux of this. Yeah, I understand that it is necessary to take the time to go through tutorials, but it's frustratingly slow. I guess I will have to go through it any which ways. Thank you again!
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