Evidence map›Paper›PMID 29528370›Full record

ArticleBioinformatics (Oxford, England)2018

METHCOMP: a special purpose compression platform for DNA methylation data.

Jianhao Peng, Olgica Milenkovic, Idoia Ochoa

Open access · bronzeAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Jianhao PengElectrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Olgica MilenkovicElectrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Idoia OchoaElectrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
University of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DNA MethylationSoftwareAlgorithmsData CompressionGenomicsHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID29528370
PMCPMC6061799
OpenAlexW2794092198

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.