Evidence map›Paper›PMID 31874601›Full record

ArticleBMC bioinformatics2019

CSA: a web service for the complete process of ChIP-Seq analysis.

Min Li, Li Tang, Fang-Xiang Wu, Yi Pan, Jianxin Wang

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. HBMC bioinformatics · 2025
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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

5 authors.

Min LiSchool of Computer Science and Engineering, Central South University, Changsha, China. limin@mail.csu.edu.cn.ORCID http://orcid.org/0000-0002-0188-1394
Li TangSchool of Computer Science and Engineering, Central South University, Changsha, China.
Fang-Xiang WuDivision of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, SKS7N5A9, Saskatoon, Canada.
Yi PanDepartment of Computer Science, Georgia State University, GA30303, Atlanta, USA.
Jianxin WangSchool of Computer Science and Engineering, Central South University, Changsha, China.

Funding

National Natural Science Foundation of China 61732009
6 · The paper itself

Abstract

backgroundChromatin immunoprecipitation sequencing (ChIP-seq) is a technology that combines chromatin immunoprecipitation (ChIP) with next generation of sequencing technology (NGS) to analyze protein interactions with DNA. At present, most ChIP-seq analysis tools adopt the command line, which lacks user-friendly interfaces. Although some web services with graphical interfaces have been developed for ChIP-seq analysis, these sites cannot provide a comprehensive analysis of ChIP-seq from raw data to downstream analysis.

resultsIn this study, we develop a web service for the whole process of ChIP-Seq Analysis (CSA), which covers mapping, quality control, peak calling, and downstream analysis. In addition, CSA provides a customization function for users to define their own workflows. And the visualization of mapping, peak calling, motif finding, and pathway analysis results are also provided in CSA. For the different types of ChIP-seq datasets, CSA can provide the corresponding tool to perform the analysis. Moreover, CSA can detect differences in ChIP signals between ChIP samples and controls to identify absolute binding sites.

conclusionsThe two case studies demonstrate the effectiveness of CSA, which can complete the whole procedure of ChIP-seq analysis. CSA provides a web interface for users, and implements the visualization of every analysis step. The website of CSA is available at http://CompuBio.csu.edu.cn.

Indexed as

High-Throughput Nucleotide SequencingSoftwareBinding SitesChromatin ImmunoprecipitationChIP-seqDownstream analysisPeak callingQuality controlVisualization

Identifiers

PMID31874601
PMCPMC6929326

What OpenQuestion holds

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LicenceCC BY
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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.