ArticleBMC genomics2020
MethylStar: A fast and robust pre-processing pipeline for bulk or single-cell whole-genome bisulfite sequencing data.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Mapping genetic modifiers of epimutation rates identifies VIM2/4 as dosage-sensitive negative regulators of CG methylation maintenance.Nature plants · 2026Article
- Integrative methylome and transcriptome analysis reveals genotype and sequence context-specific responses to aluminum stress in rice.Frontiers in plant science · 2026Article
- The technology landscape for detection of DNA methylation in cancer liquid biopsies.Epigenetics · 2025Review
- Accelerated growth increases the somatic epimutation rate in trees.Nature communications · 2025Article
- Single-cell DNA methylation analysis tool Amethyst resolves distinct non-CG methylation patterns in human astrocytes and oligodendrocytes.Communications biology · 2025Article
- A comprehensive guide to genomeZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Review
- AutoMethyc: an automated methylation analysis for massively parallel sequencing data.Briefings in bioinformatics · 2025Article
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- aPEAch: Automated Pipeline for End-to-End Analysis of Epigenomic and Transcriptomic Data.Biology · 2024Article
- Harbinger transposon insertion in ethylene signaling gene leads to emergence of new sexual forms in cucurbits.Nature communications · 2024Article
- Mapping parental DMRs predictive of local and distal methylome remodeling in epigenetic F1 hybrids.Life science alliance · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing.PLoS computational biology · 2023Article
- Computational Methods for Single-cell DNA Methylome Analysis.Genomics, proteomics & bioinformatics · 2023Review
- Single-Cell DNA Methylation Analysis in Cancer.Cancers · 2022Review
- Article
- Molecular properties of epimutation hotspots.Nature plants · 2022Article
- AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants.Genome biology · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhole-Genome Bisulfite Sequencing (WGBS) is a Next Generation Sequencing (NGS) technique for measuring DNA methylation at base resolution. Continuing drops in sequencing costs are beginning to enable high-throughput surveys of DNA methylation in large samples of individuals and/or single cells. These surveys can easily generate hundreds or even thousands of WGBS datasets in a single study. The efficient pre-processing of these large amounts of data poses major computational challenges and creates unnecessary bottlenecks for downstream analysis and biological interpretation.
resultsTo offer an efficient analysis solution, we present MethylStar, a fast, stable and flexible pre-processing pipeline for WGBS data. MethylStar integrates well-established tools for read trimming, alignment and methylation state calling in a highly parallelized environment, manages computational resources and performs automatic error detection. MethylStar offers easy installation through a dockerized container with all preloaded dependencies and also features a user-friendly interface designed for experts/non-experts. Application of MethylStar to WGBS from Human, Maize and A. thaliana shows favorable performance in terms of speed and memory requirements compared with existing pipelines.
conclusionsMethylStar is a fast, stable and flexible pipeline for high-throughput pre-processing of bulk or single-cell WGBS data. Its easy installation and user-friendly interface should make it a useful resource for the wider epigenomics community. MethylStar is distributed under GPL-3.0 license and source code is publicly available for download from github https://github.com/jlab-code/MethylStar . Installation through a docker image is available from http://jlabdata.org/methylstar.tar.gz.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.