Churros: a Docker-based pipeline for large-scale epigenomic analysis.

Autor:	Wang J; School of Biomedical Sciences, Hunan University, Changsha, Hunan, China.; Institute for Quantitative Biosciences, The University of Tokyo, Bunkyo-ku, Tokyo, Japan., Nakato R; Institute for Quantitative Biosciences, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
Jazyk:	angličtina
Zdroj:	DNA research : an international journal for rapid publication of reports on genes and genomes [DNA Res] 2024 Feb 01; Vol. 31 (1).
DOI:	10.1093/dnares/dsad026
Abstrakt:	The epigenome, which reflects the modifications on chromatin or DNA sequences, provides crucial insight into gene expression regulation and cellular activity. With the continuous accumulation of epigenomic datasets such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) data, there is a great demand for a streamlined pipeline to consistently process them, especially for large-dataset comparisons involving hundreds of samples. Here, we present Churros, an end-to-end epigenomic analysis pipeline that is environmentally independent and optimized for handling large-scale data. We successfully demonstrated the effectiveness of Churros by analyzing large-scale ChIP-seq datasets with the hg38 or Telomere-to-Telomere (T2T) human reference genome. We found that applying T2T to the typical analysis workflow has important impacts on read mapping, quality checks, and peak calling. We also introduced a useful feature to study context-specific epigenomic landscapes. Churros will contribute a comprehensive and unified resource for analyzing large-scale epigenomic data. (© The Author(s) 2023. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)
Databáze:	MEDLINE
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