Thank a lot. I'll try as you suggested.
I am an immunologist with very little background in bioinformatics; I can use basic functions in R. So, please bear with me. 1. I have classified TCGA breast cancer patient IDs based on their immune profiles into two groups. 2. I have downloaded TCGA breast cancer RNA-seq data from Xena and Firehose (level 3 normalised and non-normalised). Now, I want to arrange gene expression data into two groups based on my classification in STEP 1. The simple thing i could come up with is to open Firehose data in excel and copy-paste act patients gene expression data one by one into new excel sheet. But, due to data size (cell numbers) i am going crazy. Please help me out here and suggest a simple way to do this in R. I have all the patients IDs already copy-pasted into two groups in excel sheet. Thanks in advance.
1 answer
Hey, you just need to do:
- Save patient ID lists as TSV or CSV and then read into R via
read.table(),read.csv(),fread(), or something else. Eventually you should save these in a vector in R as, e.g.,group1IDsandgroup2IDs - Read the expression data into R - it should already be downloaded as TSV (I think)
- Subset the expression data based on the patient IDs
Small queries relating to each step can be found via a search in your search engine of choice.
Kevin
It worked fine. Thanks again.
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