Evidence map›Paper›PMID 32424069›Full record

ArticleGenome research2020

MEDEA: analysis of transcription factor binding motifs in accessible chromatin.

Luca Mariani, Kathryn Weinand, Stephen S Gisselbrecht, Martha L Bulyk

Abstract readEvaluation Study
In one paragraph

Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. ELF5-Mediated Enhancer-Promoter Interaction Regulates LALBA Expression in Ovine Mammary Gland.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  10. Computational biology approaches for mapping transcriptional regulatory networks.Computational and structural biotechnology journal · 2021
    Review
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

4 authors.

Luca Mariani *Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.ORCID 0000-0002-3502-7364
Kathryn Weinand *Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.ORCID 0000-0001-8491-7251
Stephen S GisselbrechtDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.ORCID 0000-0001-8723-902X
Martha L BulykDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.ORCID 0000-0002-3456-4555

Funding

Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Surveying transcription factor pioneer interactions with nucleosomal DNAR21HG009268 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI BULYK, MARTHA L · 2016 to 2019
$1.4M
NHGRI NIH HHS R21 HG009268NHGRI NIH HHS T32 HG002295
6 · The paper itself

Abstract

Deciphering the interplay between chromatin accessibility and transcription factor (TF) binding is fundamental to understanding transcriptional regulation, control of cellular states, and the establishment of new phenotypes. Recent genome-wide chromatin accessibility profiling studies have provided catalogs of putative open regions, where TFs can recognize their motifs and regulate gene expression programs. Here, we present motif enrichment in differential elements of accessibility (MEDEA), a computational tool that analyzes high-throughput chromatin accessibility genomic data to identify cell-type-specific accessible regions and lineage-specific motifs associated with TF binding therein. To benchmark MEDEA, we used a panel of reference cell lines profiled by ENCODE and curated by the ENCODE Project Consortium for the ENCODE-DREAM Challenge. By comparing results with RNA-seq data, ChIP-seq peaks, and DNase-seq footprints, we show that MEDEA improves the detection of motifs associated with known lineage specifiers. We then applied MEDEA to 610 ENCODE DNase-seq data sets, where it revealed significant motifs even when absolute enrichment was low and where it identified novel regulators, such as NRF1 in kidney development. Finally, we show that MEDEA performs well on both bulk and single-cell ATAC-seq data. MEDEA is publicly available as part of our Glossary-GENRE suite for motif enrichment analysis.

Indexed as

Regulatory Elements, TranscriptionalBinding SitesCell LineCell LineageChromatinDNAHumansNucleotide MotifsSequence Analysis, DNATranscription FactorsChromatinDNATranscription Factors

Identifiers

PMID32424069
PMCPMC7263192

What OpenQuestion holds

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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.