Genetic association testing using the GENESIS R/Bioconductor package

Abstract

Summary The Genomic Data Storage (GDS) format provides efficient storage and retrieval of genotypes measured by microarrays and sequencing. We developed GENESIS to perform various single- and aggregate-variant association tests using genotype data stored in GDS format. GENESIS implements highly flexible mixed models, allowing for different link functions, multiple variance components and phenotypic heteroskedasticity. GENESIS integrates cohesively with other R/Bioconductor packages to build a complete genomic analysis workflow entirely within the R environment. Availability and implementation https://bioconductor.org/packages/GENESIS; vignettes included. Supplementary information Supplementary data are available at Bioinformatics online.

A mobile sex-determining region, male-specific haplotypes, and rearing environment influence age at maturity in Chinook salmon

“…First, a kinship matrix was created using KING (Manichaikul et al 2010). Second, principle component analysis using PC-Air (Gogarten et al 2019) was performed on the kinship matrix to generate ancestry representative principle components that describe population structure while accounting for relatedness. Third, the ancestry representative principle components and SNP genotypes were used as input to PCrelate (Gogarten et al 2019) to obtain pairwise kinship coefficients which were then transformed into the GRM.…”

Genome Resequencing, Improvement of Variant Calling, and Population Genomic Analyses Provide Insights into the Seedlessness in the GenusVitis

“…Seeded and seedless traits were encoded as binary traits of 1 (control) and 2 (case), respectively. Case-control logistic mixed model association test was performed using GENESIS (Gogarten et al 2019) with default logistic mixed model association parameters assessed by Shenstone et al (2018). The Manhattan plots of XP-CLR scores and logistic association p-values were constructed using qqman (Turner 2018) in R package.…”

Efficient Calculation of the Genomic Relationship Matrix

“…Then, the calculation of the GRM needs of order sn 2 arithmetic operations. Most software packages use floating-point arithmetics, for instance the R packages AGHmatrix [3], qgg [4], rrBLUP [5], snpReady [6], and GENESIS [7]. The software GCTA [8] treats missings explicitly.…”