Title | switchBox: an R package for k-Top Scoring Pairs classifier development. |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Afsari B, Fertig EJ, Geman D, Marchionni L |
Journal | Bioinformatics |
Volume | 31 |
Issue | 2 |
Pagination | 273-4 |
Date Published | 2015 Jan 15 |
ISSN | 1367-4811 |
Keywords | Algorithms, Biomarkers, Tumor, Breast Neoplasms, Computational Biology, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Neoplasm Recurrence, Local, Support Vector Machine |
Abstract | UNLABELLED: k-Top Scoring Pairs (kTSP) is a classification method for prediction from high-throughput data based on a set of the paired measurements. Each of the two possible orderings of a pair of measurements (e.g. a reversal in the expression of two genes) is associated with one of two classes. The kTSP prediction rule is the aggregation of voting among such individual two-feature decision rules based on order switching. kTSP, like its predecessor, Top Scoring Pair (TSP), is a parameter-free classifier relying only on ranking of a small subset of features, rendering it robust to noise and potentially easy to interpret in biological terms. In contrast to TSP, kTSP has comparable accuracy to standard genomics classification techniques, including Support Vector Machines and Prediction Analysis for Microarrays. Here, we describe 'switchBox', an R package for kTSP-based prediction. AVAILABILITY: The 'switchBox' package is freely available from Bioconductor: http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
DOI | 10.1093/bioinformatics/btu622 |
Alternate Journal | Bioinformatics |
PubMed ID | 25262153 |
Grant List | K25 CA141053 / CA / NCI NIH HHS / United States UL1 RR 025005 / RR / NCRR NIH HHS / United States |
Related Lab:
Related Faculty:
Luigi Marchionni, M.D., Ph.D.