R/cnmtf.R

In lgl15/cnmtf: Prioritisation of single nucleotide variants using Corrected non-negative matrix tri-factorisation

#' @title Read me first!!
#' @description cNMTF: Prioritisation of single nucleotide variants using Corrected non-negative matrix tri-factorisation
#'
#' A data fusion framework for prioritising reliable associations between single nucleotide variants (SNVs) and traits.
#' This algorithm allows for studying the effect of SNVs on categorical traits, thanks to its main features : 1) It captures the interrelatedness between variants data, the SNVs deleteriousness effect and the protein-protein interactions (PPIs) that might be disrupted.  2) It simultaneously accounts for the patient's outcome and ancestry by means of kernels functions, minimizing the confounding for population structures.
#'
#' The \strong{cnmtf} package provides four categories of functions for
#' preprocessing data, clustering, scoring SNVs and comparing results.
#'
#' @section Preprocessing functions:
#' These functions will help you to create the inputs for the algorithm.
#'
#' @section Factorisation functions:
#' Main functions to integrate the input data, generate the low-dimmensional matrices and find consensus clusters.
#'
#' @section Scoring functions:
#' A set of functions to score SNVs and prioritise significant SNV-trait associations from the low-dimmensional matrices.
#'
#' @section Comparing functions:
#' Auxiliary functions to compare your results across different settings of the algorithm.
#'
#' @md
#' @author Luis G. Leal, \email{lgl15@@imperial.ac.uk}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


	about.cnmtf = function(){ cat("Type ?about.cnmtf for package documentation.")}