Identifying strengths and weaknesses of methods for computational network inference from single-cell RNA-seq data

Abstract Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regula...

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Veröffentlicht in:	G3 : genes - genomes - genetics Jg. 13; H. 3
Hauptverfasser:	McCalla, Sunnie Grace, Fotuhi Siahpirani, Alireza, Li, Jiaxin, Pyne, Saptarshi, Stone, Matthew, Periyasamy, Viswesh, Shin, Junha, Roy, Sushmita
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	US Oxford University Press 09.03.2023 Genetics Society of America
Schlagworte:	Algorithms Animals BASIC BIOLOGICAL SCIENCES benchmarking Datasets Gene Expression Profiling Gene Expression Regulation Gene Regulatory Networks Genetics & Heredity Humans Investigation Mice network inference algorithms Neurofibromin 2 prior knowledge Saccharomyces cerevisiae Sequence Analysis, RNA - methods Single-Cell Analysis - methods Single-Cell Gene Expression Analysis single-cell RNA-seq network inference algorithms single-cell RNA-seq gene regulatory networks benchmarking prior knowledge
ISSN:	2160-1836, 2160-1836
Online-Zugang:	Volltext
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