GCA-package: GCA: Genetic connectedness analysis
In HaipengU/Connectedness: Genetic Connectedness Analysis

Description Details Available functions in GCA package Author(s)

An R package for genetic connectedness analysis across units using pedigree and genomic data.

This package implements three connectedness metrics which are functions of prediction error variance (PEV) matrix, including prediction error variance of difference (PEVD), coefficient of determination (CD) and prediction error correlation (r), coupled with three summary methods for each statistic. For example, the PEVD across units is summarized as 1) average PEV of all pairwise differences between individuals across units; 2) average PEV within and across units; 3) using a contrast vector. Analogous summary methods will be also applied to CD and r statistics. Three additional metrics approximating connectedness using variance of estimates of unit effects (VE) are included, such as variance of estimates of units effects difference (VED), coefficient of determination of VED (CDVED), and connectedness rating (CR). Within each metric, three different methods are names according to the number of corrected factors (e.g., 0, 1 and 2) for fixed effects, such as VED0, VED1 and VED2. Similar corrected function is also applied for metrics of CDVED and CR.

computeA(): Computation of numerator relationship matrix.
computeG(): Computation of genomic relationship matrix.
gca(): Measures of genetic connectedness.
varcomp(): Estimates of variance components using eigenvalues and eigenvectors.

Haipeng Yu and Gota Morota

Maintainer: Haipeng Yu haipengyu@vt.edu

HaipengU/Connectedness documentation built on July 3, 2019, 12:21 p.m.