Title: Create Area-Proportional Venn Diagrams from Biological Lists
Description: Creates an area-proportional Venn diagram of 2 or 3 circles. 'BioVenn' is the only R package that can automatically generate an accurate area-proportional Venn diagram by having only lists of (biological) identifiers as input. Also offers the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text and numbers can be dragged and dropped. Based on the BioVenn web interface available at <https://www.biovenn.nl>. Hulsen et al. (2008) <doi:10.1186/1471-2164-9-488>.
Imports: biomaRt, graphics, grDevices, plotrix, svglite
Author: Tim Hulsen [aut, cre] (<https://orcid.org/0000-0002-0208-8443>)

Description: Creates an area-proportional Venn diagram of 2 or 3 circles. 'BioVenn' is the only R package that can automatically generate an accurate area-proportional Venn diagram by having only lists of (biological) identifiers as input. Also offers the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text and numbers can be dragged and dropped. Based on the BioVenn web interface available at <https://www.biovenn.nl>. Hulsen (2021) <doi:10.3233/DS-210032>.

Title: Access the Bioconductor Project Package Repository
Description: A convenient tool to install and update Bioconductor packages.
person("Martin", "Morgan", email = "martin.morgan@roswellpark.org",
person("Marcel", "Ramos", email = "marcel.ramos@roswellpark.org",
Suggests: BiocVersion, remotes, testthat, knitr
Author: Martin Morgan [aut] (<https://orcid.org/0000-0002-5874-8148>),

Suggests: BiocStyle, BiocVersion, remotes, testthat, withr, curl, knitr

Suggests: BiocVersion, remotes, rmarkdown, testthat, withr, curl, knitr

Suggests: BiocStyle, BiocVersion, remotes, testthat, knitr

Suggests: BiocStyle, BiocVersion, remotes, testthat, knitr, withr

Title: Feature Selection and Classification with the Embedded
Validation Procedures for Biomedical Data Analysis
Author: Natalia Novoselova,Junxi Wang,Frank Pessler,Frank Klawonn
Description: Contains functions for the data analysis with the emphasis on biological data, including several algorithms for feature ranking, feature selection, classification
algorithms with the embedded validation procedures.
The functions can deal with numerical as well as with nominal features. Includes also the functions for calculation
of feature AUC (Area Under the ROC Curve) and HUM (hypervolume under manifold) values and construction 2D- and 3D- ROC curves.
Biocomb provides the calculation of Area Above the RCC (AAC) values and construction of Relative Cost Curves
(RCC) to estimate the classifier performance under unequal misclassification costs problem.
Biocomb has the special function to deal with missing values, including different imputing schemes.