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

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单位: [1]Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. [2]Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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关键词: TCGAplot TCGA Pan-cancer analysis Visualization User-defned function

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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.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 ).© 2023. The Author(s).

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出版当年[2022]版:
大类 | 4 区 生物学
小类 | 3 区 数学与计算生物学 4 区 生化研究方法 4 区 生物工程与应用微生物
最新[2025]版:
大类 | 4 区 生物学
小类 | 3 区 生物工程与应用微生物 4 区 生化研究方法 4 区 数学与计算生物学
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出版当年[2021]版:
Q2 BIOCHEMICAL RESEARCH METHODS Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
最新[2023]版:
Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q2 BIOCHEMICAL RESEARCH METHODS Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

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第一作者单位: [1]Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. [2]Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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