Evidence map›Paper›PMID 26484757›Full record

ArticlePLoS computational biology2015

Perm-seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-Enhanced Read Mapping.

Xin Zeng, Bo Li, Rene Welch, Constanza Rojo, Ye Zheng, Colin N Dewey, Sündüz Keleş

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Mobile genomics: tools and techniques for tackling transposons.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Review
  7. Article
  8. Article
  9. 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

7 authors at 2 institutions in 1 country.

Xin ZengDepartment of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.
Bo LiCalifornia Institute for Quantitative Biosciences, University of California, Berkeley, California, United States of America.
Rene WelchDepartment of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.
Constanza RojoDepartment of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.
Ye ZhengDepartment of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.
Colin N DeweyDepartment of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America.
Sündüz KeleşDepartment of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America.
University of Wisconsin–Madison · USUniversity of California, Berkeley · US

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
NHGRI NIH HHS HG003747NHGRI NIH HHS R01 HG003747NHGRI NIH HHS U01 HG007019
6 · The paper itself

Abstract

Segmental duplications and other highly repetitive regions of genomes contribute significantly to cells' regulatory programs. Advancements in next generation sequencing enabled genome-wide profiling of protein-DNA interactions by chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq). However, interactions in highly repetitive regions of genomes have proven difficult to map since short reads of 50-100 base pairs (bps) from these regions map to multiple locations in reference genomes. Standard analytical methods discard such multi-mapping reads and the few that can accommodate them are prone to large false positive and negative rates. We developed Perm-seq, a prior-enhanced read allocation method for ChIP-seq experiments, that can allocate multi-mapping reads in highly repetitive regions of the genomes with high accuracy. We comprehensively evaluated Perm-seq, and found that our prior-enhanced approach significantly improves multi-read allocation accuracy over approaches that do not utilize additional data types. The statistical formalism underlying our approach facilitates supervising of multi-read allocation with a variety of data sources including histone ChIP-seq. We applied Perm-seq to 64 ENCODE ChIP-seq datasets from GM12878 and K562 cells and identified many novel protein-DNA interactions in segmental duplication regions. Our analysis reveals that although the protein-DNA interactions sites are evolutionarily less conserved in repetitive regions, they share the overall sequence characteristics of the protein-DNA interactions in non-repetitive regions.

Indexed as

AlgorithmsBase SequenceChromatin ImmunoprecipitationChromosome MappingDNADNA-Binding ProteinsHigh-Throughput Nucleotide SequencingHumansK562 CellsMolecular Sequence DataProtein Interaction MappingRepetitive Sequences, Nucleic AcidSegmental Duplications, GenomicDNADNA-Binding Proteins

Identifiers

PMID26484757
PMCPMC4618727
OpenAlexW2149736721

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.