PLoS Computational BiologyBioinformaticsPeer-reviewed journal article
scAmpi - A versatile pipeline for single-cell RNA-seq analysis from basics to clinics
Anne BertoliniiD, Michael PrummeriD, Mustafa Anıl TunceliD, Ulrike Menzel, María L. Rosano-GonzáleziD, Jack KuipersiD, Daniel Johannes StekhoveniD, Niko BeerenwinkeliD, Franziska SingeriD
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.
- organism: human
- assay: scRNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: experimental assay
- Citations
- 13
- FWCI
- 1.06
- Field percentile
- top 26%
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