Evidence map›Paper›PMID 25161225›Full record

ArticleBioinformatics (Oxford, England)2014

Broad-Enrich: functional interpretation of large sets of broad genomic regions.

Raymond G Cavalcante, Chee Lee, Ryan P Welch, Snehal Patil, Terry Weymouth, Laura J Scott, Maureen A Sartor

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  4. Review
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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.

Raymond G CavalcanteDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Chee LeeDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Ryan P WelchDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Snehal PatilDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Terry WeymouthDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Laura J ScottDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Maureen A SartorDepartment of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
DESIGN AND ANALYSIS OF HUMAN GENE MAPPING STUDIESR01HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 1993 to 2016
$5.5M
Proteogenomics of Cancer Training ProgramT32CA140044 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAO, ARVIND, SARTOR, MAUREEN AGNES · 2010 to 2024
$3.9M
Integrative epigenomic/genomic profiling and biomarker discovery in HPV+ and HPV-R01CA158286 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROZEK, LAURA, SARTOR, MAUREEN AGNES · 2011 to 2015
$2.6M
Design and Analysis of Human Gene Mapping StudiesR56HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 2017 to 2017
$400k
NCI NIH HHS R01 CA158286NCI NIH HHS R01CA158286-01A1NCI NIH HHS T32 CA140044NHGRI NIH HHS R01 HG000376NHGRI NIH HHS R56 HG000376NHGRI NIH HHS T32 HG000040NHGRI NIH HHS T32-HG000040NIEHS NIH HHS P30 ES017885NIEHS NIH HHS P30-ES017885-01A1
6 · The paper itself

Abstract

motivationFunctional enrichment testing facilitates the interpretation of Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data in terms of pathways and other biological contexts. Previous methods developed and used to test for key gene sets affected in ChIP-seq experiments treat peaks as points, and are based on the number of peaks associated with a gene or a binary score for each gene. These approaches work well for transcription factors, but histone modifications often occur over broad domains, and across multiple genes.

resultsTo incorporate the unique properties of broad domains into functional enrichment testing, we developed Broad-Enrich, a method that uses the proportion of each gene's locus covered by a peak. We show that our method has a well-calibrated false-positive rate, performing well with ChIP-seq data having broad domains compared with alternative approaches. We illustrate Broad-Enrich with 55 ENCODE ChIP-seq datasets using different methods to define gene loci. Broad-Enrich can also be applied to other datasets consisting of broad genomic domains such as copy number variations. AVAILABILITY AND IMPLEMENTATION: http://broad-enrich.med.umich.edu for Web version and R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Cell LineChromatin ImmunoprecipitationGenetic LociGenomicsHigh-Throughput Nucleotide SequencingHistonesHumansLogistic ModelsSequence Analysis, DNATranscription FactorsHistonesTranscription Factors

Identifiers

PMID25161225
PMCPMC4147897

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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.