Evidence map›Paper›PMID 30702424›Full record

ArticleeLife2019

Generative modeling of multi-mapping reads with mHi-C advances analysis of Hi-C studies.

Ye Zheng, Ferhat Ay, Sunduz Keles

Abstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Influence ofGenome research · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Influence ofbioRxiv : the preprint server for biology · 2025
    Article
  8. Hidden origami inmBio · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Regulation and function of transposable elements in cancer genomes.Cellular and molecular life sciences : CMLS · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Ye ZhengDepartment of Statistics, University of Wisconsin-Madison, Madison, United States.ORCID 0000-0002-8806-2761
Ferhat AyLa Jolla Institute for Allergy and Immunology, La Jolla, United States.
Sunduz KelesDepartment of Statistics, University of Wisconsin-Madison, Madison, United States.ORCID 0000-0001-9048-0922

Funding

Statistical Methods for the Analysis of ChlP-chip DataR01HG003747 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI KELES, SUNDUZ · 2007 to 2024
$4.8M
Statistical Methods For Annotating Repetitive Genomic Regions Through ENCODE-deriU01HG007019 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI BRESNICK, EMERY H, DEWEY, COLIN NOEL · 2012 to 2015
$1.5M
Statistical methods for profiling long-range interactions of repetitive genomic regions with Hi-C dataR21HG009744 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI KELES, SUNDUZ · 2018 to 2019
$395k
La Jolla Institute for Allergy and Immunology Institute Leadership FundsNHGRI NIH HHS HG007019NHGRI NIH HHS HG009744NHGRI NIH HHS R01 HG003747NHGRI NIH HHS R21 HG009744NHGRI NIH HHS U01 HG007019
6 · The paper itself

Abstract

Current Hi-C analysis approaches are unable to account for reads that align to multiple locations, and hence underestimate biological signal from repetitive regions of genomes. We developed and validated

Indexed as

Cell LineChromatinComputer SimulationEnhancer Elements, GeneticGenomicsHumansProbabilityPromoter Regions, GeneticReproducibility of ResultsChromatinchromosome chromatin capturecomputational biologyHi-Chumanmousemulti-readsprobabilistic modelingsystems biology

Identifiers

PMID30702424
PMCPMC6450682

What OpenQuestion holds

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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.