Evidence map›Paper›PMID 28499349›Full record

ArticleBMC bioinformatics2017

Epimetheus - a multi-profile normalizer for epigenomic sequencing data.

Mohamed-Ashick M Saleem, Marco-Antonio Mendoza-Parra, Pierre-Etienne Cholley, Matthias Blum, Hinrich Gronemeyer

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  3. Review
  4. Article
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 at 2 institutions in 1 country.

Mohamed-Ashick M SaleemEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.
Marco-Antonio Mendoza-ParraEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. marco@igbmc.u-strasbg.fr.
Pierre-Etienne CholleyEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.
Matthias BlumEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.
Hinrich GronemeyerEquipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. hg@igbmc.u-strasbg.fr.ORCID http://orcid.org/0000-0001-9454-2449
Centre National de la Recherche Scientifique · FRInstitut de génétique et de biologie moléculaire et cellulaire · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene regulatory mechanisms. One of today's challenges for such studies is to identify functionally informative local and global patterns of chromatin states in order to describe the regulatory impact of the epigenome in normal cell physiology and in case of pathological aberrations. Critically, the most preferred Chromatin ImmunoPrecipitation-Sequencing (ChIP-Seq) is inherently prone to significant variability between assays, which poses significant challenge on comparative studies. One challenge concerns data normalization to adjust sequencing depth variation.

resultsCurrently existing tools either apply linear scaling corrections and/or are restricted to specific genomic regions, which can be prone to biases. To overcome these restrictions without any external biases, we developed Epimetheus, a genome-wide quantile-based multi-profile normalization tool for histone modification data and related datasets.

conclusionsEpimetheus has been successfully used to normalize epigenomics data in previous studies on X inactivation in breast cancer and in integrative studies of neuronal cell fate acquisition and tumorigenic transformation; Epimetheus is freely available to the scientific community.

Indexed as

High-Throughput Nucleotide SequencingSequence Analysis, DNACell DifferentiationCell LineChromatinChromatin ImmunoprecipitationEpigenomicsHep G2 CellsHistonesHumansTretinoinChromatinHistonesTretinoinChIP-seqEpigenomeMulti-sample analysisQuantile-based data normalization

Identifiers

PMID28499349
PMCPMC5429578
OpenAlexW2612303102

What OpenQuestion holds

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LicenceCC BY
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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.