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DIRAC specifications


Unique identifier OMICS_14391
Alternative name Differential Rank Conservation
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Gene expression matrix, fixed network, expression matrix for network genes
Output data Rank template, rank matching score, rank conservation index, rank difference score
Operating system Unix/Linux, Mac OS, Windows
Programming languages MATLAB
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Nathan Price

Publication for Differential Rank Conservation

DIRAC citations


Integrating the dysregulated inflammasome based molecular functionome in the malignant transformation of endometriosis associated ovarian carcinoma

PMCID: 5790494
PMID: 29423077
DOI: 10.18632/oncotarget.23364

[…] The regulation of the GO terms were quantified by the GSR model, which converted gene expression profiles to quantified functions by the modifying the Differential Rank Conservation (DIRAC) [] algorithm. This model quantifies the ordering change of the gene elements in a gene set between the gene expression orderings in ES, CCC or EC and the most co […]


Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis Associated Ovarian Carcinoma Using a Data Driven, Function Based Analysis

Int J Mol Sci
PMCID: 5713314
PMID: 29113136
DOI: 10.3390/ijms18112345

[…] The detail of the GSR model and the computing procedures are described in our previous study [,]. Briefly, the GSR model converted gene expression profiles to quantified functions with the differential rank conservation (DIRAC) [] algorithm, which measures the ordering change of the gene elements in a gene set between the gene expression orderings in ES, CCC or EC and the most common ge […]


Gene Set−Based Integrative Analysis Revealing Two Distinct Functional Regulation Patterns in Four Common Subtypes of Epithelial Ovarian Cancer

Int J Mol Sci
PMCID: 5000670
PMID: 27527159
DOI: 10.3390/ijms17081272

[…] The algorithm of computing the GSR indices was modified from the Differential Rank Conservation (DIRAC). DIRAC is designed to measure the perturbation of a gene set by converting gene expression levels to gene expression rankings, and quantifying the regularity of […]


Gene Set Based Functionome Analysis of Pathogenesis in Epithelial Ovarian Serous Carcinoma and the Molecular Features in Different FIGO Stages

Int J Mol Sci
PMCID: 4926420
PMID: 27275818
DOI: 10.3390/ijms17060886

[…] The GSR index is computed by modified Differential Rank Conservation (DIRAC) [], an algorithm measuring the ordering perturbations of gene elements in a gene set. In contrast to gene set perturbation, the GSR model quantifies the ordering […]


Gene interaction enrichment and network analysis to identify dysregulated pathways and their interactions in complex diseases

BMC Syst Biol
PMCID: 3426489
PMID: 22694839
DOI: 10.1186/1752-0509-6-65

[…] epresented by the co-variances or correlations between case and control classes, and showed that this approach provides biologically meaningful results []. Eddy et al. developed another method called DIfferential RAnk Conservation (DIRAC), which is based on the relative expression ranks of genes in a pathway [,]. A limitation of this method, however, is that it assesses the change in the relations […]


Molecular signatures from omics data: From chaos to consensus

Biotechnol J
PMCID: 3418428
PMID: 22528809
DOI: 10.1002/biot.201100305

[…] l changes in gene expression data, and more recent proposals have also been made. One recently developed approach to identifying pathway-based molecular signatures for phenotype classification is the Differential Rank Conservation (DIRAC) method []. Unlike GSEA or other enrichment methods that usually return p-values for gene set enrichment, DIRAC builds a network-based molecular signature that id […]


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DIRAC institution(s)
Institute for Genomic Biology, University of Illinois, Urbana, IL, USA; Department of Bioengineering, University of Illinois, Urbana, IL, USA; Institute for Systems Biology, Seattle, WA, USA; Center for Biophysics and Computational Biology, University of Illinois, Urbana, IL, USA; Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana, IL, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
DIRAC funding source(s)
This work was supported by an NIH-NCI Howard Temin Pathway to Independence Award in Cancer Research, an NIH Center for Systems Biology GM076547, Department of Defense Grant W81XWH-08-1-0420, as well as funding from Grand Duchy of Luxembourg-Institute for Systems Biology Program and by NIH-NCRR Grant UL1 RR 025005 and by NSF CCF-0625687.

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