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BioinformaticsGenome Medicine
Peer-reviewed journal article

Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq

Coral Fustero TorreiD, María José Jiménez‐SantosiD, Santiago García‐MartíniD, Carlos Carretero-PucheiD, Luis García-Jimeno, Vadym IvanchukiD, Tomás Di DomenicoiD, Gonzalo Goméz-LópeziD, Fátima Al‐ShahrouriD

Abstract

We present Beyondcell (https://gitlab.com/bu_cnio/beyondcell/), a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines therapeutic differences among cell populations, and generates a prioritised ranking of the differential sensitivity drugs between chosen conditions to guide drug selection. We performed Beyondcell analysis in four single-cell datasets to validate our score and to demonstrate that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients.

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