How to analyze TCGA data downloaded by TCGA2STAT using TCGAbiolinks package

Question

[J. Smith]

Hello Friends,

I have downloaded TCGA data (gene expression, methylation) using TCGA2STAT. Now, I want to use TCGAbiolinks package for performing subsequent analysis. I want to know what function I may use to convert my already downloaded data using TCGA2STAT compatible for using TCGAbiolinks functions like TCGAanalyze_Preprocessing, TCGAvisualize_meanMethylation, etc.? I think I need to convert my data into SummarizedExperiment format. But I don't know how to convert TCGA2STAT data into SummarizedExperiment format. Please help.

Answer 1

[Kevin Blighe]

Just download the initial data using TCGAbiolinks itself.

Kevin

[J. Smith]

Thanks Kevin. Actually I am facing problem with the GDCprepare() function when using TCGAbiolinks. I am getting error "Killed after 2 h" in RStudio, probably because my machine is not of so high configuration. If you please tell me, if there is any way to find differentially methylated regions/CpGs and later to find their associated genes using data downloaded through TCGA2STAT? Please do mention if there are other packages/functions for downloading and processing data to solve my problem due to machine configuration, if possible.

[Kevin Blighe]

I have not used TCGA2STAT, unfortunately. If I may suggest that you download a single table of normalised methylation values from UCSC Xena:

• https://xenabrowser.net/datapages/?host=https%3A%2F%2Ftcga.xenahubs.ne...

That may bypass much of the extra processing work with which your computer appears to struggle.

[J. Smith]

Thanks a lot Kevin. I have downloaded it. Now, as I want to apply TCGAvisualize_meanMethylation, TCGAanalyze_DMR and other functions, I have to convert it into SummarizedExperiment format. I am struggling to do it. Is there any easy function available for it?

[J. Smith]

Hi Kevin. Greetings of the Day!!!

I have obtained TCGA RNAseq - IlluminaHiSeq data from UCSC Xena. They have downloaded Level_3 data from TCGA DCC (file names: *.rsem.genes.normalized_results) and log2(x+1) transformed.

I want to find differentially expressed genes from for particular cancer, say, for LIHC using primary solid tumour and solid tissue normal samples using the data obtained from there.

I know that packages like DESeq2 and EdgeR are widely used to find differentially expressed genes for RNASeq data. But they require raw counts data. I have also used R packages like limma and SAM to find differentially expressed genes from DNA Microarray data.

But I don't know which packages or methods are good to find differentially expressed genes from RNASeq rsem and log2(x+1) transformed data as I have collected above.

[Kevin Blighe]

Hey, you can use the Xena HTseq data by converting it back to raw counts, as to which I elaborate here: A: Normalisation of RNAseq data from UCSC Xena Browser

Then, use those in EdgeR or DESeq2.

Does that help:

[J. Smith]

Thanks so much Kevin.