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TOP

TOP Constructs Transferable Model Across Gene Expression Platforms

Bioconductor version: 3.23 · Package version: 1.12.0

TOP constructs a transferable model across gene expression platforms for prospective experiments. Such a transferable model can be trained to make predictions on independent validation data with an accuracy that is similar to a re-substituted model. The TOP procedure also has the flexibility to be adapted to suit the most common clinical response variables, including linear response, binomial and Cox PH models.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("TOP")

Details

MaintainerHarry Robertson <harry.robertson@sydney.edu.au>
AuthorHarry Robertson [aut, cre] (ORCID: <https://orcid.org/0000-0001-9203-3894>), Nicholas Robertson [aut]
LicenseGPL-3
URLhttps://github.com/Harry25R/TOP
Bug Reportshttps://github.com/Harry25R/TOP/issues
Downloads rank214
Source branchRELEASE_3_23
biocViewsGeneExpression, Software, Survival

Documentation

Download

Dependencies

Depends: R (>= 4.1.0)

Imports: assertthat, caret, ClassifyR, directPA, doParallel, dplyr, ggnewscale, ggplot2, ggraph, ggrepel, ggthemes, glmnet, Hmisc, igraph, latex2exp, limma, magrittr, methods, plotly, pROC, purrr, reshape2, stats, stringr, survival, tibble, tidygraph, tidyr, statmod

Suggests: knitr, rmarkdown, BiocStyle, Biobase, curatedOvarianData, ggbeeswarm, ggsci, survminer, tidyverse

Reverse dependencies

Suggests Me (1): ClassifyR