Generates tree plots with precise branch lengths, gene annotations, and cellular prevalence. The package handles complex tree structures (angles, lengths, etc.) and can be further refined as needed by the user.

Functions to perform the following analyses: i) inferring epistasis from RNAi double knockdown data; ii) identifying gene pairs of multiple mutation patterns; iii) assessing association between gene pairs and survival; and iv) calculating the smallworldness of a graph (e.g., a gene interaction network).  Data and analyses are described in Wang, X., Fu, A. Q., McNerney, M. and White, K. P. (2014). Widespread genetic epistasis among breast cancer genes. Nature Communications. 5 4828. <doi:10.1038/ncomms5828>.

Predicts anticancer peptides using random forests trained on the
    n-gram encoded peptides. The implemented algorithm can be accessed from
    both the command line and shiny-based GUI. The CancerGram model is too large 
    for CRAN and it has to be downloaded separately from the repository:
    <https://github.com/BioGenies/CancerGramModel>. For more information see: 
    Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>.

Classifies the type of cancer using routinely collected data
    commonly found in cancer registries from pathology reports. The
    package implements the International Classification of Diseases for
    Oncology, 3rd Edition site (topography), histology (morphology), and behaviour codes of neoplasms to classify cancer type 
    <https://www.who.int/standards/classifications/other-classifications/international-classification-of-diseases-for-oncology>. 
    Classification in children utilize the International Classification of Childhood Cancer by Steliarova-Foucher et al. (2005) <doi:10.1002/cncr.20910>.
    Adolescent and young adult cancer classification is based on Barr et al. (2020) <doi:10.1002/cncr.33041>.

Retrieve cancer screening data for cervical, breast and colorectal
    cancers from the Kenya Health Information System <https://hiskenya.org> in a 
    consistent way.