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ssGSEA on RNA-Seq data from TCGA

Hi:

Given TCGA RNA-Seq data (level 3), how one can do single sample GSEA?

For example, TCGA RNA-Seq data has

Gene      Raw counts     RPKM
ALK       434            2.3
..        ..             ..

Can we create a GCT file of Raw counts or RPKM to ssGSEA in gene pattern?

Thanks
Adrian

rna-seq gene

Hi,

ssGSEA in comparison with GSEA calculates separate enrichment scores for each pairing of a sample and gene set.

However, both need the .GCT files as an input. From the TCGA you need to download the level 3 data, however it has to be expression. So, after some preprocessing your .GCT should look like this:

#1.2
no. of rows       no. of columns
NAME Description Sample1 Sample2 ...
gene1 NA               exp. value
gene2 NA
...

I think that there is no possibility to calculate those statistics from raw counts and rpkm. Raw counts may be biased, so I think that you should consider some normalisation step for such analysis to make it comparable with other studies.

Best regards!

Could anyone explain how ssGSEA process the gene expression data to rank the gene for each patient sample? Dose it need to be compared with the normal sample?

1 answer

I know this is an old thread, but SSGSEA can be calculated using the Bioconductor package GSVA. If you use RPKM, use ssgsea <- gsva (RPKM, method="ssgsea", kcdf="Gaussian", ...); if you use raw counts, use ssgsea <- gsva (counts, method="ssgsea", kcdf="Poisson", ...)

I think kcdf parameter is only applicable when method = "gsva". According to the docs:

Character string denoting the kernel to use during the non-parametric estimation of the cumulative distribution function of expression levels across samples when method="gsva".

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