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.
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.
Authors: Allen S Yang; Marcos R H Estécio; Ketan Doshi; Yutaka Kondo; Eloiza H Tajara; Jean-Pierre J Issa Journal: Nucleic Acids Res Date: 2004-02-18 Impact factor: 16.971
Authors: Qiang Song; Benjamin Decato; Elizabeth E Hong; Meng Zhou; Fang Fang; Jianghan Qu; Tyler Garvin; Michael Kessler; Jun Zhou; Andrew D Smith Journal: PLoS One Date: 2013-12-06 Impact factor: 3.240