Evidence map›Paper›PMID 39256681›Full record

ArticleBMC bioinformatics2024

HiCMC: High-Efficiency Contact Matrix Compressor.

Yeremia Gunawan Adhisantoso, Tim Körner, Fabian Müntefering, Jörn Ostermann, Jan Voges

Abstract read
In one paragraph

Article in BMC bioinformatics, 2024. 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
–field-weighted citation impact
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.

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

5 authors.

Yeremia Gunawan AdhisantosoInstitut für Informationsverarbeitung and L3S Research Center, Leibniz University Hannover, Hannover, Germany. adhisant@tnt.uni-hannover.de.
Tim KörnerInstitut für Informationsverarbeitung and L3S Research Center, Leibniz University Hannover, Hannover, Germany.
Fabian MünteferingInstitut für Informationsverarbeitung and L3S Research Center, Leibniz University Hannover, Hannover, Germany.
Jörn OstermannInstitut für Informationsverarbeitung and L3S Research Center, Leibniz University Hannover, Hannover, Germany.
Jan VogesCIMA University of Navarra, Pamplona, Spain.

Funding

German Federal Ministry of Education and Research (BMBF) 01EK2204F
6 · The paper itself

Abstract

backgroundChromosome organization plays an important role in biological processes such as replication, regulation, and transcription. One way to study the relationship between chromosome structure and its biological functions is through Hi-C studies, a genome-wide method for capturing chromosome conformation. Such studies generate vast amounts of data. The problem is exacerbated by the fact that chromosome organization is dynamic, requiring snapshots at different points in time, further increasing the amount of data to be stored. We present a novel approach called the High-Efficiency Contact Matrix Compressor (HiCMC) for efficient compression of Hi-C data.

resultsBy modeling the underlying structures found in the contact matrix, such as compartments and domains, HiCMC outperforms the state-of-the-art method CMC by approximately 8% and the other state-of-the-art methods cooler, LZMA, and bzip2 by over 50% across multiple cell lines and contact matrix resolutions. In addition, HiCMC integrates domain-specific information into the compressed bitstreams that it generates, and this information can be used to speed up downstream analyses.

conclusionHiCMC is a novel compression approach that utilizes intrinsic properties of contact matrix, such as compartments and domains. It allows for a better compression in comparison to the state-of-the-art methods. HiCMC is available at https://github.com/sXperfect/hicmc .

Indexed as

ChromosomesAlgorithmsComputational BiologyHumansSoftware3CCompressionContact matrixHi-C

Identifiers

PMID39256681
PMCPMC11389233

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.