Evidence map›Paper›PMID 25741452›Full record

ArticleQuantitative biology (Beijing, China)2013

Computational methodology for ChIP-seq analysis.

Hyunjin Shin, Tao Liu, Xikun Duan, Yong Zhang, X Shirley Liu

Abstract read
In one paragraph

Article in Quantitative biology (Beijing, China), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Statistical Analysis in ChIP-seq-Related Applications.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Facilitating Analysis of Publicly Available ChIP-Seq Data for Integrative Studies.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Single molecule and single cell epigenomics.Methods (San Diego, Calif.) · 2015
    Review
  20. 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

5 authors.

Hyunjin ShinDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health, Boston, MA 02115, USA.
Tao LiuDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health, Boston, MA 02115, USA.
Xikun DuanDepartment of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 200092, China.
Yong ZhangDepartment of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 200092, China.
X Shirley LiuDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute/Harvard School of Public Health, Boston, MA 02115, USA.

Funding

Computational Models for Mechanisms of Global Transcription RegulationR01HG004069 · NHGRI · DANA-FARBER CANCER INST · PI LIU, XIAOLE SHIRLEY · 2006 to 2013
$3.6M
NHGRI NIH HHS R01 HG004069
6 · The paper itself

Abstract

Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) is a powerful technology to identify the genome-wide locations of DNA binding proteins such as transcription factors or modified histones. As more and more experimental laboratories are adopting ChIP-seq to unravel the transcriptional and epigenetic regulatory mechanisms, computational analyses of ChIP-seq also become increasingly comprehensive and sophisticated. In this article, we review current computational methodology for ChIP-seq analysis, recommend useful algorithms and workflows, and introduce quality control measures at different analytical steps. We also discuss how ChIP-seq could be integrated with other types of genomic assays, such as gene expression profiling and genome-wide association studies, to provide a more comprehensive view of gene regulatory mechanisms in important physiological and pathological processes.

Identifiers

PMID25741452
PMCPMC4346130

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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.