Differential gene set analysis on TCGA data

Question

[hsnikdo]

I am totally new to bioinformatics. I would like to use the Bioconductor package in R to determine how expression profiles compare between samples with high expression and low expression of a gene of interest. First, I need to subset TCGA by subtype to account for "noise."

Example: Looking within the TCGA-BRCA dataset, how do I query strictly Basal-like samples? And how then can I separate into high expression and low expression groups for a single gene of interest?

Answer 1

[Elucidata]

The Xena Browser provides an interactive framework to query TCGA datasets. You can select the TCGA-BRCA dataset in the Xena Browser and use PAM_50_mRNA_nature2012 annotation to classify samples into different subtypes, one of them is Basal-like.

You can download the sample vs annotation mapping and complete expression data as well from the browser. Now further in R, you can classify the samples based on your needs in two steps:

Step 1. You can subset your samples to those matching Basal-like in the annotation file.

Step 2. There can be several methods to segregate samples based on the high and low expression of a gene, one method could be to calculate quartiles on the expression of your gene of interest. Based on the quartile cutoffs, you can select the first quartile as the low expression samples and the fourth quartile as the high expression samples. You can pull out sample names corresponding to both these groups and add that as an annotation for further downstream processing.

[Ram]

Hi,

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[Elucidata]

Hi, we do not intend to spam or break any other rules on Biostars. We respect all the forum rules. As a company we did not join to advertise our products, we just want to help our community. We just want to add our quick links as a signature, like other forums allow to do.

[Ram]

Please do not use your link as a signature - we do not encourage this behavior. Advertise your blog on a separate post.