How to use TCGAbiolinks to analyze expression profile data in TCGA
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For transcriptome data, difference analysis and enrichment analysis is one of the core analysis contents. TCGA expression profile data download, difference analysis and enrichment analysis can be easily realized through TCGAbiolinks. Taking the gene expression profile of breast cancer as an example, the analysis process is as follows.
1. Download raw data
Because of the large number of breast cancer samples in TCGA, only some samples were selected for testing. The download process is as follows
two。 Difference analysis
The detailed steps are as follows
The data are preprocessed, and the samples with low correlation are removed according to the Spelman correlation coefficient between samples.
Normalization, calling the normalization algorithm in EDASeq
Screening genes according to the mean value of expression
Difference analysis, calling the difference algorithm in edgeR
The code is as follows
3. Enrichment analysis
The code is as follows
The visualization results are as follows
Three categories of GO plus four categories of kegg pathway data, corresponding to four bar charts, each bar chart shows the top10 items with the most significant FDR value, Abscissa I-log10 (FDR), scatter represents GeneRatio, also known as enrich factor, represents the proportion of the number of differential genes enriched to the total number of genes in this pathway.
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