fastGMA

fastGMA is a C++ toolkit for genomic mixed-model analysis of complex traits. It provides efficient methods for:

genome-wide association studies (GWAS),
variance component and heritability estimation, and
genomic prediction.

Modules

Mode	Purpose	Guide
`--make-grm`, `--process-grm`	Build additive, dominance and epistatic GRMs; merge, convert, invert and decompose GRMs	GRM
`--uvlmm`	Univariate linear mixed model with one or more GRMs	uvLMM
`--remma`	Rapid linear mixed model for non-additive analysis	REMMA
`--glmm`	Generalized linear mixed model for binary traits	GLMM
`--mvlmm`	Multivariate linear mixed model for several correlated traits	mvLMM
`--longwas`	Longitudinal data analysis with random regression models	lonGWAS
`--fast-reml`	REML estimation of genetic, GxE and heteroscedastic noise variances	fastREML

fastgma -h lists all modes, and fastgma -h <n> prints the full option list of mode n.

Inputs and outputs

Genotypes: PLINK binary files (--bfile <prefix> for .bed, .bim, .fam) or a feature matrix (--ffile <prefix> for .fmat, .bim, .fam), for every module except fastREML, which reads only GRMs.
Phenotypes and covariates: a whitespace-separated table with a header row and the individual ID in the first column. Traits, covariates and class variables are selected by column name.
GRMs: three files that share one prefix, given as --grm <prefix>:
- <prefix>.grm.bin: the lower triangle of the GRM including the diagonal, stored row by row (\(A_{11}, A_{21}, A_{22}, A_{31}, \ldots\)) as little-endian float32.
- <prefix>.grm.id: one line per individual (FID IID), in the row order of the matrix.
- <prefix>.grm.N.bin: the number of SNPs used for each pair of individuals, in the same layout as .grm.bin.
GRMs are built with fastgma --make-grm (see GRM). This is the GCTA binary GRM format, so a GRM built by fastgma can be used directly in GCTA, and a GRM built by GCTA can be used directly in every fastgma module.

Quick start

# 1. Additive GRM
fastgma --make-grm --bfile test --out test

# 2. Mixed-model GWAS with heritability estimation
fastgma --uvlmm --grm test --bfile test \
  --data pheno.txt --trait height --covar age --class sex \
  --out height

See Installation to download fastgma.

Contact

If you have questions, please open an issue on GitHub or email ningchao91@gmail.com.