TimiGP: An R package to depict the tumor microenvironment from bulk transcriptomics

Chenyang Li; Jianjun Zhang; Chao Cheng

doi:10.1016/j.xpro.2023.102742

TimiGP: An R package to depict the tumor microenvironment from bulk transcriptomics

STAR Protoc. 2023 Dec 15;4(4):102742. doi: 10.1016/j.xpro.2023.102742. Epub 2023 Nov 27.

Authors

Chenyang Li¹, Jianjun Zhang², Chao Cheng³

Affiliations

¹ Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, TX 77030, USA. Electronic address: [email protected].
² Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, TX 77030, USA; Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Lung Cancer Genomics Program, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Lung Cancer Interception Program, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: [email protected].
³ Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; The Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA. Electronic address: [email protected].

Abstract

Exploring the clinical relevance of diverse immune cell types within the tumor microenvironment is pivotal for unraveling cancer intricacies and developing treatments. Here, we present a protocol for using tumor immune microenvironment illustration based on gene pairs, an R package to deduce cell-cell interactions, unveiling the association between immune cell relative abundance and patient prognoses from bulk gene expression and survival data. We describe steps for harnessing cell-type markers derived from single-cell RNA sequencing data to map the tumor immune microenvironment across a spectrum of cancer types. For complete details on the use and execution of this protocol, please refer to Li et al. (2023).¹.

Keywords: Bioinformatics; Cancer; Gene Expression; Genomics; Immunology; RNA-seq; Single Cell; Systems biology.

MeSH terms

Cell Communication
Gene Expression Profiling
Humans
Neoplasms* / genetics
Tumor Microenvironment* / genetics

Abstract

MeSH terms

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