TCGAplot: an R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data

被引:10
|
作者
Liao, Chenqi [1 ,2 ]
Wang, Xiong [1 ]
机构
[1] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Lab Med, Wuhan, Peoples R China
[2] Huazhong Univ Sci & Technol, Tongji Med Coll, Wuhan, Peoples R China
关键词
TCGAplot; TCGA; Pan-cancer analysis; Visualization; User-defined function;
D O I
10.1186/s12859-023-05615-3
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: Pan-cancer analysis examines both the commonalities and heterogeneity among genomic and cellular alterations across numerous types of tumors. Pan-cancer analysis of gene expression, tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TIME), and methylation becomes available based on the multi-omics data from The Cancer Genome Atlas Program (TCGA). Some online tools provide analysis of gene and protein expression, mutation, methylation, and survival for TCGA data. However, these online tools were either Uni-functional or were not able to perform analysis of user-defined functions. Therefore, we created the TCGAplot R package to facilitate perform pan-cancer analysis and visualization of the built-in multi-omic TCGA data.Results: TCGAplot provides several functions to perform pan-cancer paired/unpaired differential gene expression analysis, pan-cancer correlation analysis between gene expression and TMB, MSI, TIME, and promoter methylation. Functions for visualization include paired/unpaired boxplot, survival plot, ROC curve, heatmap, scatter, radar chart, and forest plot. Moreover, gene set based pan-cancer and tumor specific analyses were also available. Finally, all these built-in multi-omic data could be extracted for implementation for user-defined functions, making the pan-cancer analysis much more convenient.\Conclusions: We developed an R-package for integrative pan-cancer analysis and visualization of TCGA multi-omics data. The source code and pre-built package are available at GitHub (https://github.com/tjhwangxiong/TCGAplot).
引用
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页数:15
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