DOI: 10.18129/B9.bioc.netDx    

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see netDx.

Network-based patient classifier

Bioconductor version: 3.11

netDx is a general-purpose algorithm to build a patient classifier from heterogenous patient data. The method converts data into patient similarity networks at the level of features. Feature selection identifies features of predictive value to each class. Methods are provided for versatile predictor design and performance evaluation using standard measures. netDx natively groups molecular data into pathway-level features and connects with Cytoscape for network visualization of pathway themes. For method details see: Pai et al. (2019). netDx: interpretable patient classification using integrated patient similarity networks. Molecular Systems Biology. 15, e8497

Author: Shraddha Pai [aut, cre] , Philipp Weber [aut], Ahmad Shah [aut], Luca Giudice [aut], Shirley Hui [aut], Ruth Isserlin [aut], Luca Giudice [aut], Hussam Kaka [aut], Gary Bader [aut]

Maintainer: Shraddha Pai <shraddha.pai at>

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HTML R Script 01. Build binary predictor and view performance, top features and integrated Patient Similarity Network
HTML R Script 02. Build three-way classifier (N-way; N>2) from multi-omic data
HTML R Script 03. Build classifier from sparse genetic data
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biocViews BiomedicalInformatics, Classification, Network, Software, SystemsBiology
Version 1.0.4
In Bioconductor since BioC 3.11 (R-4.0) (0.5 years)
License MIT + file LICENSE
Depends R (>= 3.6)
Imports ROCR, pracma, ggplot2, RCy3, glmnet, igraph, reshape2, parallel, stats, utils, MultiAssayExperiment, graphics, grDevices, methods, BiocFileCache, GenomicRanges, bigmemory, doParallel, foreach, combinat, rappdirs, GenomeInfoDb, S4Vectors, IRanges, RColorBrewer, scater, netSmooth, clusterExperiment, Rtsne
Suggests curatedTCGAData, TCGAutils, rmarkdown, testthat, knitr
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