how to correct gene expression based on tumor purity

Question

[liu4gre]

Hi all, I am looking at TCGA gene expression data. Also I am interested in tumor purity, which may be inferred by a few tools such as ABSOLUTE and ESTIMATE. Question is how to correct gene expression levels based on these inferred values?

[Alejandro Jimenez Sanchez]

Hi have you found an answer to this? For differential expression analysis using RNAseq data, it seems the package DESeq2 has a function that allows you to correct for purity estimates. See this paper: https://www.nature.com/articles/ncomms9971

[rummy.chowdhury]

Hi, I am wondering if you figured out the answer to your question? I have the same question with regards to how to apply the tumor purity value to the gene expression levels?? I was able to calculate the tumor purity for each TCGA case for my cancer of interest. But now I'm unsure as to how to apply it. Please do let me know if you were able to get a better understanding of how to work with tumor purity.

Thank you

[Shixiang]

I have same question

Answer 1

[Kevin Blighe]

You just need to include it as a covariate in your design formula. While not directly modifying your data to adjust for the purity estimate, doing this will adjust the statistical inferences made from that data.

Kevin

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Edit: November 12, 2018:

Some evidence to back this:

"In conclusion, we have shown that the influence of tumour purity on the results of genomic analyses is much stronger than previously appreciated, and ought to be included as a covariate in any future analysis."

[source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671203/]

It is refuted here, though, and stated that purities estimate should be multiplicative:

"There are some practices to account for purity in differential expression (DE) analysis [46] by adding purities as a covariate in the linear model. As we will show, the purity should have a multiplicative effect instead of an additive effect."

[source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5267453/]

[Chun-Jie Liu]

But if the the purity value is numeric, how to add it into design formula? To classify samples as low, median and high?

Is there a method to adjust the gene expression by tumor purity?

[Kevin Blighe]

A covariate can be categorical or numeric. I am not aware of a program that directly adjusts for tumor purity (but one likely exists... somewhere).

Answer 2

[catechize.2.learn]

Hi,

You may look at this article:

contamDE-lm: linear model-based differential gene expression analysis using next-generation RNA-seq data from contaminated tumor samples

https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btaa006/5698700