Package: maPredictDSC 1.51.0

Adi Laurentiu Tarca

maPredictDSC: Phenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge

This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types.

Authors:Adi Laurentiu Tarca <[email protected]>

maPredictDSC_1.51.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
maPredictDSC/json (API)

# Install 'maPredictDSC' in R:

install.packages('maPredictDSC', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

On BioConductor:maPredictDSC-1.51.0(bioc 3.24)maPredictDSC-1.50.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarray classification

3.30 score 2 scripts 1 mentions 3 exports 120 dependencies

Last updated from:c471e01dff. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	226
linux-devel-x86_64	NOTE	413
source / vignettes	OK	354
linux-release-x86_64	NOTE	415
macos-release-arm64	NOTE	216
macos-oldrel-arm64	NOTE	224
windows-devel	NOTE	344
windows-release	NOTE	323
windows-oldrel	NOTE	347
wasm-release	OK	209

Exports:aggregateDSC perfDSC predictDSC

Dependencies:affy affyio AnnotationDbi askpass Biobase BiocGenerics BiocManager Biostrings bit bit64 bitops blob cachem caret caTools class cli clock codetools cpp11 crayon curl data.table DBI diagram digest dplyr e1071 evaluate farver fastmap foreach future future.apply gcrma generics ggplot2 globals glue gower gplots gtable gtools hardhat hgu133plus2.db highr httr ipred IRanges isoband iterators jsonlite KEGGREST KernSmooth knitr labeling lattice lava lifecycle limma listenv lubridate LungCancerACvsSCCGEO magrittr MASS Matrix memoise mime ModelMetrics nlme nnet numDeriv openssl org.Hs.eg.db parallelly pillar pkgconfig plyr png preprocessCore pROC prodlim progressr proxy purrr R6 RColorBrewer Rcpp recipes reshape2 rlang ROC ROCR rpart RSQLite S4Vectors S7 scales Seqinfo shape sparsevctrs SQUAREM statmod stringi stringr survival sys tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr xfun XVector yaml

maPredictDSC

Overview | Developing prediction models with maPredictDSC package

Rendered frommaPredictDSC.Rnwusingutils::Sweave

Last update: 2013-11-01
Started: 2013-11-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Combine predictions from several fitted models fitted with predictDSC	aggregateDSC
Area Under the Precision-Recall Curve (AUPR), Belief Confusion Metric (BCM) and Correct Class Enrichment Metric (CCEM).	perfDSC
Phenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge	predictDSC