maPredictDSC statistics

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maPredictDSC specifications


Unique identifier OMICS_14613
Name maPredictDSC
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.18.0
Stability Stable
AnnotationDbi, limma, parallel, R(>=2.15.0), affy, MASS, class, ROC, ROCR, gcrma, e1071, hgu133plus2.db, caret, LungCancerACvsSCCGEO
Maintained Yes



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  • person_outline Adi Laurentiu Tarca <>

Publication for maPredictDSC

maPredictDSC in publication

PMCID: 4379164
PMID: 25822971
DOI: 10.1371/journal.pone.0118573

[…] a five time repeated three-fold cross validation procedure on the training data that included both the ratios ranking and lda model fitting steps, functionality that we have made available in the mapredictdsc package [] of bioconductor ( the sensitivity estimate of the resulting model for the optimal number of top ratios was determined for each possible normalizer […]

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maPredictDSC institution(s)
Department of Computer Science, Wayne State University, Detroit, MI, USA; Perinatology Research Branch, NICHD/NIH, Detroit, MI, USA; The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Rovereto, Italy; ETH Zurich, Zurich, Switzerland; IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA; Philip Morris International, Research & Development, Neuchâtel, Switzerland
maPredictDSC funding source(s)
This work was partly supported by Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (N01-HD-2-3342), by DSC best overall performer grant from Philip Morris International, by the Swiss National Science Foundation (PP00P2_128503) and by, the Swiss Initiative for Systems Biology.

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