Provide functionality for cancer subtyping using nearest centroids or machine learning methods based on TCGA data.

Construct and evaluate directed tree structures that
   model the process of occurrence of genetic alterations during carcinogenesis
   as described in Szabo, A. and Boucher, K (2002)  <doi:10.1016/S0025-5564(02)00086-X>.

Measures different aspects of page content, structure and performance for SEO (Search Engine Optimization).
    Aspects covered include HTML tags used in SEO, duplicate and near-duplicate content, structured data, on-site linking structure and popularity transfer, and many other amazing things. 
    This package can be used to generate a real, full SEO audit report, which serves to detect errors or inefficiencies on a page that can be corrected in order to optimise its performance on search engines.

Single-cell datasets are growing in size, posing challenges as well as opportunities for biology researchers. 'ondisc' (short for "on-disk single cell") enables users to easily and efficiently analyze large-scale single-cell data. 'ondisc' makes computing on large-scale single-cell data FUN: Fast, Universal, and iNtuitive.

Designed to enhance data validation and management processes by employing a set of functions that read a set of rules from a 'CSV' or 'Excel' file and apply them to a dataset. Funded by the National Renewable Energy Laboratory and Possibility Lab, maintained by the Moore Institute for Plastic Pollution Research.

Two-stage design for single-arm phase II 
		trials with time-to-event endpoints (e.g., clinical trials on 
		immunotherapies among cancer patients) can be calculated using this package. 
		Two notable advantages of the package: 1) It provides flexible choices from 
		three design methods (optimal, minmax, and admissible), and 2) the power of
		the design is more accurately calculated using the exact variance in the
		one-sample log-rank test. The package can be used for 1) planning the sample
		sizes and other design parameters, and 2) conducting the interim and final
		analyses for the Go/No-go decisions. More details about the design method
		can be found in: Wu, J, Chen L, Wei J, Weiss H, Chauhan A. (2020).
		<doi:10.1002/pst.1983>.