Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods

Autor: Karamveer, Yasin Uzun
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Bioinformatics and Biology Insights, Vol 18 (2024)
Druh dokumentu: article
ISSN: 1177-9322
11779322
DOI: 10.1177/11779322241287120
Popis: Gene regulatory networks are powerful tools for modeling genetic interactions that control the expression of genes driving cell differentiation, and single-cell sequencing offers a unique opportunity to build these networks with high-resolution genomic data. There are many proposed computational methods to build these networks using single-cell data, and different approaches are used to benchmark these methods. However, a comprehensive discussion specifically focusing on benchmarking approaches is missing. In this article, we lay the GRN terminology, present an overview of common gold-standard studies and data sets, and define the performance metrics for benchmarking network construction methodologies. We also point out the advantages and limitations of different benchmarking approaches, suggest alternative ground truth data sets that can be used for benchmarking, and specify additional considerations in this context.
Databáze: Directory of Open Access Journals
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