Evidence map›Paper›PMID 30986246›Full record

ArticlePLoS computational biology2019

MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments.

Ivan Juric, Miao Yu, Armen Abnousi, Ramya Raviram, Rongxin Fang, Yuan Zhao, Yanxiao Zhang, Yunjiang Qiu, Yuchen Yang, Yun Li and 2 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing 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

87 citing papers in PubMed.

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  17. Unveiling Multi-Scale Architectural Features in Single-Cell Hi-C Data Using scCAFE.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  18. Article
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27 more citing papers are in PubMed but not listed here.

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

12 authors.

Ivan JuricDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, United States of America.
Miao YuLudwig Institute for Cancer Research, La Jolla, CA, United States of America.
Armen AbnousiDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, United States of America.
Ramya RaviramLudwig Institute for Cancer Research, La Jolla, CA, United States of America.
Rongxin FangLudwig Institute for Cancer Research, La Jolla, CA, United States of America.
Yuan ZhaoLudwig Institute for Cancer Research, La Jolla, CA, United States of America.ORCID 0000-0001-8471-872X
Yanxiao ZhangLudwig Institute for Cancer Research, La Jolla, CA, United States of America.ORCID 0000-0001-9618-637X
Yunjiang QiuLudwig Institute for Cancer Research, La Jolla, CA, United States of America.ORCID 0000-0002-0539-9714
Yuchen YangDepartments of Genetics, Biostatistics, and Computer Science, University of North Carolina, Chapel Hill, NC, United States of America.ORCID 0000-0001-5977-1617
Yun LiDepartments of Genetics, Biostatistics, and Computer Science, University of North Carolina, Chapel Hill, NC, United States of America.ORCID 0000-0002-9275-4189
Bing RenLudwig Institute for Cancer Research, La Jolla, CA, United States of America.
Ming HuDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, United States of America.ORCID 0000-0003-0987-2916

Funding

San Diego Center for 4D Nucleome ResearchU54DK107977 · NIDDK · LUDWIG INSTITUTE FOR CANCER RES LTD · PI MURRE, CORNELIS, REN, BING · 2015 to 2019
$9.4M
Genetic Studies of Blood Cell Traits in Multi-Ethnic CohortsR01HL129132 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, YUN, REINER, ALEXANDER P · 2016 to 2019
$2.7M
NHLBI NIH HHS R01 HL129132NIDDK NIH HHS U54 DK107977
6 · The paper itself

Abstract

Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range chromatin interactions genome-wide at reduced cost and enhanced resolution, but extracting information from the resulting datasets has been challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq and HiChIP, to process the data from such experiments and identify long-range chromatin interactions. MAPS adopts a zero-truncated Poisson regression framework to explicitly remove systematic biases in the PLAC-seq and HiChIP datasets, and then uses the normalized chromatin contact frequencies to identify significant chromatin interactions anchored at genomic regions bound by the protein of interest. MAPS shows superior performance over existing software tools in the analysis of chromatin interactions from multiple PLAC-seq and HiChIP datasets centered on different transcriptional factors and histone marks. MAPS is freely available at https://github.com/ijuric/MAPS.

Indexed as

ChromatinChromatin Assembly and DisassemblyChromatin ImmunoprecipitationChromosome MappingComputational BiologyComputer SimulationGenomeGenomicsHigh-Throughput Nucleotide SequencingHistone CodeHumansSequence Analysis, DNASoftwareChromatin

Identifiers

PMID30986246
PMCPMC6483256

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Registered trials

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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.