Evidence map›Paper›PMID 24278165›Full record

ArticlePloS one2013

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.

Jing Yang, Hui Yu, Bao-Hong Liu, Zhongming Zhao, Lei Liu, Liang-Xiao Ma, Yi-Xue Li, Yuan-Yuan Li

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

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3 · Its place in the literature

Who cites it

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

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4 · The record

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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

8 authors.

Jing YangSchool of Biotechnology, East China University of Science and Technology, Shanghai, P. R. China ; Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China.
Hui Yu
Bao-Hong Liu
Zhongming Zhao
Lei Liu
Liang-Xiao Ma
Yi-Xue Li
Yuan-Yuan Li

Funding

Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI WANG, LILY, ZHAO, ZHONGMING · 2012 to 2014
$1.0M
Understanding Genetic Basis of Dental Caries via Integrative Genomic ApproachesR03DE022093 · NIDCR · VANDERBILT UNIVERSITY · PI WANG, LILY, ZHAO, ZHONGMING · 2011 to 2012
$478k
Investigating MicroRNAs and Their Regulatory Networks in GlioblastomaR03CA167695 · NCI · VANDERBILT UNIVERSITY · PI ZHAO, ZHONGMING · 2013 to 2014
$154k
NCI NIH HHS R03 CA167695NCI NIH HHS R03CA167695NIDCR NIH HHS R03 DE022093NIDCR NIH HHS R03DE022093NLM NIH HHS R01 LM011177NLM NIH HHS R01LM011177
6 · The paper itself

Abstract

motivationDifferential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner.

resultsTo advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named "Differential Regulation Analysis" (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject.

conclusionsWith ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical. AVAILABILITY: DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.

Indexed as

SoftwareAlgorithmsGene Regulatory NetworksOligonucleotide Array Sequence Analysis

Identifiers

PMID24278165
PMCPMC3835854

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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.