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DCGL specifications


Unique identifier OMICS_12492
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 2.1.2
Stability No
Source code URL https://cran.r-project.org/web/packages/DCGL/index.html
Maintained No


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Publications for DCGL

DCGL citations


Gene Expression Analysis Reveals Novel Shared Gene Signatures and Candidate Molecular Mechanisms between Pemphigus and Systemic Lupus Erythematosus in CD4+ T Cells

Front Immunol
PMCID: 5776326
PMID: 29387060
DOI: 10.3389/fimmu.2017.01992

[…] lues using limma R package (). All the probes from each of the microarray platforms were filtered out for significant low expression/variation (P < 0.05) using the “varianceBasedfilter” function from DCGL R package (). The remaining probes were mapped to Ensembl gene identifiers and probes’ expression was collapsed to gene-level expression using “collapseRows” function with default parameters in W […]


Exploring of the molecular mechanism of rhinitis via bioinformatics methods

PMCID: 5783521
PMID: 29257233
DOI: 10.3892/mmr.2017.8213

[…] DCGL was an R package for identifying differentially co-expressed genes and links from gene expression microarray data (). It could examine the expression correlation based on the exact co-expression […]


A novel integrated gene coexpression analysis approach reveals a prognostic three transcription factor signature for glioma molecular subtypes

BMC Syst Biol
PMCID: 5009532
PMID: 27586240
DOI: 10.1186/s12918-016-0315-y

[…] In order to prioritize the regulators that are putatively causative to glioma, we first identified differentially regulated genes (DRGs) by using DCGL v2.0 [] in GSE4290, and then chose the DRGs which were significant in both Targets’ Enrichment Density (TED) analysis and Targets’ DCL Density (TDD) analysis in DCGL v2.0 []. TED analysis evaluat […]


Differential Regulatory Analysis Based on Coexpression Network in Cancer Research

Biomed Res Int
PMCID: 4997028
PMID: 27597964
DOI: 10.1155/2016/4241293

[…] n WGCNA. One limitation of WGCNA is that its GCN construction is undirected. Other prior knowledge is needed if further regulatory analysis based on GCN is designed.Link-based quantitative methods in DCGL [, ] employ a half-thresholding strategy to construct specific GCNs. That is, if at least one of the two coexpression values of a specific link exceeds the threshold, the link in both coexpressio […]


Construction of protein interaction network involved in lung adenocarcinomas using a novel algorithm

PMCID: 4998145
PMID: 27588126
DOI: 10.3892/ol.2016.4822

[…] creened across 4 datasets. Based on these DE genes, gene interaction networks were constructed, and the score value of each gene pair was obtained using the EB coexpression approach, STRING database, DCGL method and WGCNA package. A novel algorithm was applied to convert and combine the score values that were obtained from the aforementioned methods; a novel matrix with a combined score of each ge […]


Screening of biomarkers for prediction of response to and prognosis after chemotherapy for breast cancers

PMCID: 4861001
PMID: 27217777
DOI: 10.2147/OTT.S92350

[…] are frequently coexpressed, and thus, the identification of differentially coexpressed genes (DCGs) from gene expression microarray data is essential. The Differentially Coexpressed Genes and Links (DCGL) in R package (v2.0) was used to screen DCGs and links between breast cancer patients with and without chemotherapy, based on differential coexpression profile and differential coexpression enric […]


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DCGL institution(s)
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA; Departments of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN, USA; Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China; School of Biotechnology, East China University of Science and Technology, Shanghai, China; Shanghai Center for Bioinformation Technology, Shanghai Industrial Technology Institute, Shanghai, China

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