METHCOMP: a special purpose compression platform for DNA methylation data
Abstract Motivation DNA methylation is one of the most important epigenetic mechanisms in cells that exhibits a significant role in controlling gene expressions. Abnormal methylation patterns have been associated with cancer, imprinting disorders and repeat-instability diseases. As inexpensive bisul...
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Published in: | Bioinformatics Vol. 34; no. 15; pp. 2654 - 2656 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
England
Oxford University Press
01-08-2018
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Subjects: | |
Online Access: | Get full text |
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Summary: | Abstract
Motivation
DNA methylation is one of the most important epigenetic mechanisms in cells that exhibits a significant role in controlling gene expressions. Abnormal methylation patterns have been associated with cancer, imprinting disorders and repeat-instability diseases. As inexpensive bisulfite sequencing approaches have led to significant efforts in acquiring methylation data, problems of data storage and management have become increasingly important. The de facto compression method for methylation data is gzip, which is a general purpose compression algorithm that does not cater to the special format of methylation files. We propose METHCOMP, a new compression scheme tailor-made for bedMethyl files, which supports random access.
Results
We tested the METHCOMP algorithm on 24 bedMethyl files retrieved from four randomly selected ENCODE assays. Our findings reveal that METHCOMP offers an average compression ratio improvement over gzip of up to 7.5x. As an example, METHCOMP compresses a 48 GB file to only 0.9 GB, which corresponds to a 98% reduction in size.
Availability and implementation
METHCOMP is freely available at https://github.com/jianhao2016/METHCOMP.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/bty143 |