iGPSC-DB: a comprehensive database for an inferred single-cell genetic perturbation atlas

Genetic perturbation-induced transcriptional reprogramming drastically remodels tumor cellular phenotypes and tumor microenvironment crosstalk. Unraveling the heterogeneous cellular responses to genetic perturbations is essential for the mechanistic dissection of tumors and the discovery of therapeutic targets. Here, we present iGPSC-DB (https://bio-bigdata.hrbmu.edu.cn/iGPSC-DB), a database designed to infer connections between tumor microenvironmental cells and diverse genetic perturbation events and to dissect the heterogeneous cellular responses to these perturbations. iGPSC-DB curates associations linking 178 114 perturbation events that target 7407 genes to 9 249 080 single cells from 1580 samples across 88 cancer types. iGPSC-DB also provides seven user-friendly tools for retrieving and analyzing: (i) inferred associations between genetic perturbation events and cells/cell types; (ii) the inferred perturbation-associated effects of perturbations on cellular functions, developmental trajectories, and cell-cell communication within the tissue microenvironment; (iii) the combined effects of different perturbations on cells, facilitating the design of combination therapeutic regimens; (iv) the impact of different perturbations on the differentiation trajectories and functional states of malignant cells; and (v) the association between perturbed target genes and clinical survival outcomes. iGPSC-DB will serve as a valuable resource to advance single-cell-resolution research on gene functions, regulatory mechanisms, and the discovery of tumor therapeutic targets.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-11-05
DOI
https://doi.org/10.1093/nar/gkag1079
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

iGPSC-DB: a comprehensive database for an inferred single-cell genetic perturbation atlas

Zhe Chen, Yifang Zhang, Yanjun Xu, Qiuyan Guo et al.
Nucleic Acids Research
Single-cell and spatial transcriptomics
article

iGPSC-DB: a comprehensive database for an inferred single-cell genetic perturbation atlas

Zhe Chen, Yifang Zhang, Yanjun Xu, Qiuyan Guo, 康安辉, Jiangtao Xing, Feng Li, Xinyu Song, Siyao Lu, Longqi Xu, Peng Wang, Xinyi Wang
article en

Abstract

Genetic perturbation-induced transcriptional reprogramming drastically remodels tumor cellular phenotypes and tumor microenvironment crosstalk. Unraveling the heterogeneous cellular responses to genetic perturbations is essential for the mechanistic dissection of tumors and the discovery of therapeutic targets. Here, we present iGPSC-DB (https://bio-bigdata.hrbmu.edu.cn/iGPSC-DB), a database designed to infer connections between tumor microenvironmental cells and diverse genetic perturbation events and to dissect the heterogeneous cellular responses to these perturbations. iGPSC-DB curates associations linking 178 114 perturbation events that target 7407 genes to 9 249 080 single cells from 1580 samples across 88 cancer types. iGPSC-DB also provides seven user-friendly tools for retrieving and analyzing: (i) inferred associations between genetic perturbation events and cells/cell types; (ii) the inferred perturbation-associated effects of perturbations on cellular functions, developmental trajectories, and cell-cell communication within the tissue microenvironment; (iii) the combined effects of different perturbations on cells, facilitating the design of combination therapeutic regimens; (iv) the impact of different perturbations on the differentiation trajectories and functional states of malignant cells; and (v) the association between perturbed target genes and clinical survival outcomes. iGPSC-DB will serve as a valuable resource to advance single-cell-resolution research on gene functions, regulatory mechanisms, and the discovery of tumor therapeutic targets.

Nucleic Acids Research
Harbin Medical University (CN), First Affiliated Hospital of Harbin Medical University (CN)
Openalex Percentile: Top 26%
Single-cell and spatial transcriptomics
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