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Journal Article

RLM: Fast and simplified extraction of Read-Level Methylation metrics from bisulfite sequencing data

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Hetzel,  Sara
Dept. of Genome Regulation (Head: Alexander Meissner), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Gießelmann,  Pay
Dept. of Genome Regulation (Head: Alexander Meissner), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Reinert,  Knut
Efficient Algorithms for Omics Data (Knut Reinert), Max Planck Fellow Group, Max Planck Institute for Molecular Genetics, Max Planck Society;

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Meissner,  Alexander
Dept. of Genome Regulation (Head: Alexander Meissner), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Kretzmer,  Helene
Dept. of Genome Regulation (Head: Alexander Meissner), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Hetzel_2021.pdf
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Citation

Hetzel, S., Gießelmann, P., Reinert, K., Meissner, A., & Kretzmer, H. (2021). RLM: Fast and simplified extraction of Read-Level Methylation metrics from bisulfite sequencing data. Bioinformatics, 37(21), 3934-3935. doi:10.1093/bioinformatics/btab663.


Cite as: https://hdl.handle.net/21.11116/0000-0009-8BEE-F
Abstract
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.