HapMap_ASW_MXL_KINGmat

KING-robust kinship coefficient estimates for the combined HapMap African Americans in the Southwest U.S. (ASW) and Mexican Americans in Los Angeles (MXL) samples.

datasets

The GENESIS package provides methodology for estimating,
inferring, and accounting for population and pedigree structure
in genetic analyses.  The current implementation provides
functions to perform PC-AiR (Conomos et al., 2015, Gen Epi) and PC-Relate
(Conomos et al., 2016, AJHG). PC-AiR performs a Principal Components
Analysis on genome-wide SNP data for the detection of population
structure in a sample that may contain known or cryptic relatedness.
Unlike standard PCA, PC-AiR accounts for relatedness in the sample
to provide accurate ancestry inference that is not confounded by
family structure. PC-Relate uses ancestry representative principal
components to adjust for population structure/ancestry and accurately
estimate measures of recent genetic relatedness such as kinship
coefficients, IBD sharing probabilities, and inbreeding coefficients.
Additionally, functions are provided to perform efficient variance
component estimation and mixed model association testing for both
quantitative and binary phenotypes.

Matthew P Conomos

GENESIS

GENetic EStimation and Inference in Structured samples
(GENESIS): Statistical methods for analyzing genetic data from
samples with population structure and/or relatedness

HapMap_ASW_MXL_KINGmat function

The format is:
 num [1:173, 1:173] 0 0.00157 -0.00417 0.00209 0.00172 ...

Format

Source

Matrix of Pairwise Kinship Coefficient Estimates for the combined HapMap ASW and MXL Sample found with the KING-robust estimator from the KING software.

HapMap_ASW_MXL_KINGmat: Matrix of Pairwise Kinship Coefficient Estimates for the combined HapMap ASW and MXL Sample found with the KING-robust estimator from the KING software.

Description

Usage

Arguments

Value

Format

Source

References