How to analyze TCGA data downloaded by TCGA2STAT using TCGAbiolinks package
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18 months ago
J. Smith ▴ 50

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.

TCGA2STAT TCGAbiolinks summarizedExperiment • 880 views
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18 months ago

Just download the initial data using TCGAbiolinks itself.

Kevin

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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.

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

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

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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?

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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.

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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:

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Thanks so much Kevin.

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