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scAmpi-A versatile pipeline for single-cell RNA-seq analysis from basics to clinics.
Bertolini, Anne; Prummer, Michael; Tuncel, Mustafa Anil; Menzel, Ulrike; Rosano-González, María Lourdes; Kuipers, Jack; Stekhoven, Daniel Johannes; Beerenwinkel, Niko; Singer, Franziska.
Afiliação
  • Bertolini A; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland.
  • Prummer M; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland.
  • Tuncel MA; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland.
  • Menzel U; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland.
  • Rosano-González ML; ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.
  • Kuipers J; ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.
  • Stekhoven DJ; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland.
  • Beerenwinkel N; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland.
  • Singer F; ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.
PLoS Comput Biol ; 18(6): e1010097, 2022 06.
Article em En | MEDLINE | ID: mdl-35658001
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Análise de Célula Única Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Análise de Célula Única Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article