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scAmpi—A versatile pipeline for single-cell RNA-seq analysis from basics to clinics

Bertolini, Anne; Prummer, Michael; Tuncel, M A; Menzel, Ulrike; Rosano-González, María Lourdes; Kuipers, Jack; Stekhoven, Daniel Johannes; Tumor Profiler consortium; Beerenwinkel, Niko; Singer, Franziska (2022). scAmpi—A versatile pipeline for single-cell RNA-seq analysis from basics to clinics. PLoS Computational Biology, 18(6):e1010097.

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique to decipher tissue composition at the single-cell level and to inform on disease mechanisms, tumor heterogeneity, and the state of the immune microenvironment. Although multiple methods for the computational analysis of scRNA-seq data exist, their application in a clinical setting demands standardized and reproducible workflows, targeted to extract, condense, and display the clinically relevant information. To this end, we designed scAmpi (Single Cell Analysis mRNA pipeline), a workflow that facilitates scRNA-seq analysis from raw read processing to informing on sample composition, clinically relevant gene and pathway alterations, and in silico identification of personalized candidate drug treatments. We demonstrate the value of this workflow for clinical decision making in a molecular tumor board as part of a clinical study.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Modeling and Simulation
Physical Sciences > Ecology
Life Sciences > Molecular Biology
Life Sciences > Genetics
Life Sciences > Cellular and Molecular Neuroscience
Physical Sciences > Computational Theory and Mathematics
Language:English
Date:3 June 2022
Deposited On:26 Oct 2022 14:38
Last Modified:16 Jun 2025 03:41
Publisher:Public Library of Science (PLoS)
ISSN:1553-734X
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1371/journal.pcbi.1010097
PubMed ID:35658001
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