Version 1
: Received: 30 October 2024 / Approved: 31 October 2024 / Online: 1 November 2024 (08:09:20 CET)
How to cite:
Chinchilla Caravaca, J. From Single-Cell RNA Sequencing to Functional Networks: Understanding Genetic Variants in Cancer Through Perturb-seq. Preprints2024, 2024102607. https://doi.org/10.20944/preprints202410.2607.v1
Chinchilla Caravaca, J. From Single-Cell RNA Sequencing to Functional Networks: Understanding Genetic Variants in Cancer Through Perturb-seq. Preprints 2024, 2024102607. https://doi.org/10.20944/preprints202410.2607.v1
Chinchilla Caravaca, J. From Single-Cell RNA Sequencing to Functional Networks: Understanding Genetic Variants in Cancer Through Perturb-seq. Preprints2024, 2024102607. https://doi.org/10.20944/preprints202410.2607.v1
APA Style
Chinchilla Caravaca, J. (2024). From Single-Cell RNA Sequencing to Functional Networks: Understanding Genetic Variants in Cancer Through Perturb-seq. Preprints. https://doi.org/10.20944/preprints202410.2607.v1
Chicago/Turabian Style
Chinchilla Caravaca, J. 2024 "From Single-Cell RNA Sequencing to Functional Networks: Understanding Genetic Variants in Cancer Through Perturb-seq" Preprints. https://doi.org/10.20944/preprints202410.2607.v1
Abstract
This project introduces a comprehensive pipeline that integrates various bioinformatics tools and methodologies derived from extensive bibliographic research to leverage Perturb-seq, a high-throughput sequencing method, for finding complex altered protein–protein interaction (PPi) subnetworks in cancer variants. The pipeline demonstrates excellent performance, successfully distinguishes impactful, identifies variants with similar expression profiles, and shows promising results for retrieving key affected modules already observed in KRAS and TP53 variants. These promising results indicate the potential of the Perturb-seq approach to become a standard strategy for uncovering not only common significantly expressed genes, but also interactors that could be targeted in future therapeutic strategies. All code to recapitulate the analysis is available along with documentation of pipeline usage at https://github.com/jesusch10/perturbseq_analysis.
Keywords
Single-cell RNA sequencing (scRNA-seq); functional networks; genetic variants in cancer; Perturbseq; cancer genomics; KRAS; TP53; gene expression profiling; genetic perturbation
Subject
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
