find_contributors: Identification of Key Contributors

In esteinig/netviewr: Network Visualization And Population Structure

Identification of Key Contributors

Description

Identification of key contributors using Horn's Parallel Analysis, Eigenvalue Decomposition and calculation of the Genetic Contribution Score (GCS) as described in Neuditschko et al. (2017).

Usage

find_contributors(matrix, metaData, paran_iterations=100, paran_centile=99, dist=FALSE, verbose=TRUE)

Arguments

matrix	Pairwise relationship / correlation / similarity matrix between samples (N x N)
paran_iterations	Iterations for computing the number of significant components using Horn's Parallel Analysis in Paran [ int, 100 ]
paran_centile	Significance level (centile used in estimating bias) in Paran [ int, 99 ]
dist	Input matrix is a distance matrix; converted to similarity matrix by subtracting from 1 [ bool, FALSE ]
verbose	Print computation status and results of Horn's Parallel Analysis [ bool, TRUE ]

Details

For examples and tutorials, please see the Repository: https://github.com/esteinig/netviewr

Value

Tibble containing ordered genetic contribution scores (GCS)

esteinig/netviewr documentation built on Oct. 20, 2024, 5:16 a.m.