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DawnRank specifications

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Unique identifier OMICS_10915
Name DawnRank
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data The input includes differential gene expression (between tumor and normal) and somatic alteration data (point mutations or CNVs).
Output data The output includes a ranked list of mutated genes according to their DawnRank score. A high DawnRank score for an altered gene in cancer indicates that the gene is more likely to be a driver.
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 1.2
Stability No
Maintained No

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Publication for DawnRank

DawnRank citations

 (8)
library_books

Integration of multiple networks and pathways identifies cancer driver genes in pan cancer analysis

2018
BMC Genomics
PMCID: 5756345
PMID: 29304754
DOI: 10.1186/s12864-017-4423-x

[…] es in the pathways that are highly connected.The third group combines multi-omics data to overcome the mutational heterogeneity of cancer. This group includes MutsigCV [], MDPFinder [], DriverNet [], DawnRank [], iPAC [], MSEA [], NetBox [] and MeMo []. MutsigCV was applied to exome sequences and gene expression levels, while MDPFinder is an integrative model of mutation and expression data used t […]

library_books

Integrating omics data and protein interaction networks to prioritize driver genes in cancer

2017
Oncotarget
PMCID: 5601632
PMID: 28938536
DOI: 10.18632/oncotarget.19481

[…] od. As defined by the 20/20 rule, only 138 driver genes have been discovered to date. Both of these datasets were used to assess the accuracy of our method. We compared our method with the DriverNet, DawnRank, frequency-based method and MUFFINN method.In accordance with both approaches mentioned above, we used the same datasets to perform the analysis and restricted the comparisons to three tumor […]

library_books

Progression inference for somatic mutations in cancer

2017
PMCID: 5415494
PMID: 28492066
DOI: 10.1016/j.heliyon.2017.e00277

[…] DriverDB assembles together lists of the top ranked driver genes determined from the use of 15 packages, including ActiveDriver, Dendrix, MDPFinder, Simon, NetBox, OncodriveFM, MutSigCV, MEMo, CoMDP, DawnRank, DriverNet, e-Driver, iPAC, MSEA, and OncodriveCLUST. lists the cancer types, sample size, and descriptions of the driver genes used, including chromosome location, gene ontology nomenclatur […]

library_books

The use of gene interaction networks to improve the identification of cancer driver genes

2017
PeerJ
PMCID: 5274523
PMID: 28149674
DOI: 10.7717/peerj.2568

[…] mat is growing, and integration is considered at the graph level.In this paper we seek to determine if combining interaction graphs improves the identification of cancer driver genes by DriverNet and DawnRank. They were both developed using the R environment, which provides powerful data analysis and graphical features. DriverNet met the standards set by Bioconductor (). We combined graphs from Dr […]

library_books

LNDriver: identifying driver genes by integrating mutation and expression data based on gene gene interaction network

2016
BMC Bioinformatics
PMCID: 5259866
PMID: 28155630
DOI: 10.1186/s12859-016-1332-y

[…] KIRC data set, our method always remarkably outperforms GeneRank and frequency-based method (Fig. ). Although the performance of the top several genes in LNDriver is slightly worse than DriverNet and DawnRank, for latter genes, it has a remarkably better performance than DriverNet method. The curves show that the stability of our method and DawnRank is relatively good since the precision of the tw […]

library_books

iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

2016
Genome Med
PMCID: 5180414
PMID: 28007024
DOI: 10.1186/s13073-016-0390-0

[…] is given in Table . Besides computational tools that use genomic mutations as input, other tools use transcriptomic or post-transcriptomic information as input. Some tools, such as PARADIGM-SHIFT [], DawnRank [], OncoIMPACT[], and ActiveDriver [], provide personal cancer driver gene prediction. However, they require gene expression, phosphorylation, or copy number variation data from patients, all […]


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DawnRank institution(s)
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Medical Scholars Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
DawnRank funding source(s)
This work was supported by an award from the Interdisciplinary Innovation Initiative (In3) program at the University of Illinois and an Illinois Distinguished Fellowship.

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