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RLM: fast and simplified extraction of read-level methylation metrics from bisulfite sequencing data

SUMMARY: Bisulfite sequencing data provide value beyond the straightforward methylation assessment by analyzing single-read patterns. Over the past years, various metrics have been established to explore this layer of information. However, limited compatibility with alignment tools, reference genome...

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Detalles Bibliográficos
Autores principales: Hetzel, Sara, Giesselmann, Pay, Reinert, Knut, Meissner, Alexander, Kretzmer, Helene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686677/
https://www.ncbi.nlm.nih.gov/pubmed/34601556
http://dx.doi.org/10.1093/bioinformatics/btab663
Descripción
Sumario:SUMMARY: Bisulfite sequencing data provide value beyond the straightforward methylation assessment by analyzing single-read patterns. Over the past years, various metrics have been established to explore this layer of information. However, limited compatibility with alignment tools, reference genomes or the measurements they provide present a bottleneck for most groups to routinely perform read-level analysis. To address this, we developed RLM, a fast and scalable tool for the computation of several frequently used read-level methylation statistics. RLM supports standard alignment tools, works independently of the reference genome and handles most sequencing experiment designs. RLM can process large input files with a billion reads in just a few hours on common workstations. AVAILABILITY AND IMPLEMENTATION: https://github.com/sarahet/RLM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.