GENESIS-package
(Package: GENESIS) :
GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness
The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation performs 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.
● Data Source:
BioConductor
● Keywords:
● Alias: GENESIS, GENESIS-package
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assocTestMM
(Package: GENESIS) :
SNP Genotype Association Testing with Mixed Models
assocTestMM performs SNP genotype association tests using the null model fit with fitNullMM.
● Data Source:
BioConductor
● Keywords: association, mixed model
● Alias: assocTestMM
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fitNullMM
(Package: GENESIS) :
Fit a Mixed Model Under the Null Hypothesis
fitNullMM fits a mixed model with random effects specified by their covariance structures; this allows for the inclusion of a polygenic random effect using a kinship matrix or genetic relationship matrix (GRM). The output of fitNullMM can be used to estimate genetic heritability and can be passed to assocTestMM for the purpose of genetic association testing.
● Data Source:
BioConductor
● Keywords: association, mixed model, variance component
● Alias: fitNullMM
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king2mat
(Package: GENESIS) :
Convert KING text output to an R Matrix
king2mat is used to extract the pairwise kinship coefficient estimates or IBS0 values from the output text files of KING and put them into an R object of class matrix that can be read by the functions pcair and pcairPartition.
● Data Source:
BioConductor
● Keywords:
● Alias: king2mat
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pcair
(Package: GENESIS) :
PC-AiR: Principal Components Analysis in Related Samples
pcair is used to perform a Principal Components Analysis using genome-wide SNP data for the detection of population structure in a sample. Unlike a standard PCA, PC-AiR accounts for sample relatedness (known or cryptic) to provide accurate ancestry inference that is not confounded by family structure.
● Data Source:
BioConductor
● Keywords: ancestry, multivariate, robust
● Alias: pcair, print.pcair, print.summary.pcair, summary.pcair
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pcairPartition
(Package: GENESIS) :
Partition a sample into an ancestry representative 'unrelated subset' and a 'related subset'
pcairPartition is used to partition a sample from a genetic study into an ancestry representative 'unrelated subset' and a 'related subset'. The 'unrelated subset' contains individuals who are all mutually unrelated to each other and representative of the ancestries of all individuals in the sample, and the 'related subset' contains individuals who are related to someone in the 'unrealted subset'.
● Data Source:
BioConductor
● Keywords:
● Alias: pcairPartition
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pcrelate
(Package: GENESIS) :
PC-Relate: Model-Free Estimation of Recent Genetic Relatedness
pcrelate is used to estimate kinship coefficients, IBD sharing probabilities, and inbreeding coefficients using genome-wide SNP data. PC-Relate accounts for population structure (ancestry) among sample individuals through the use of ancestry representative principal components (PCs) to provide accurate relatedness estimates due only to recent family (pedigree) structure.
● Data Source:
BioConductor
● Keywords: relatedness, robust
● Alias: pcrelate
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pcrelateMakeGRM
(Package: GENESIS) :
Creates a Genetic Relationship Matrix (GRM) of Pairwise Kinship Coefficient Estimates from PC-Relate Output
pcrelateMakeGRM is used to create a genetic relationship matrix (GRM) of pairwise kinship coefficient estimates from the output of pcrelate.
● Data Source:
BioConductor
● Keywords:
● Alias: pcrelateMakeGRM
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pcrelateReadInbreed
(Package: GENESIS) :
Create a Table of Inbreeding Coefficient Estimates from PC-Relate Output
pcrelateReadInbreed is used to create a table of inbreeding coefficient estimates from the output of pcrelate.
● Data Source:
BioConductor
● Keywords:
● Alias: pcrelateReadInbreed
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pcrelateReadKinship
(Package: GENESIS) :
Create a Table of Pairwise Kinship Coefficient and IBD Sharing Probability Estimates from PC-Relate Output
pcrelateReadKinship is used to create a table of pairwise kinship coefficient and IBD sharing probability (k0, k1, k2) estimates from the output of pcrelate.
● Data Source:
BioConductor
● Keywords:
● Alias: pcrelateReadKinship
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