Multivariate {MultiABEL} | R Documentation |
The function imports GenABEL (gwaa.data class) or DatABEL (.fv*) data formats and performs multivariate test for each genetic variant using multivariate analysis of variance (MANOVA).
Multivariate(x, trait.idx = NULL, ...)
x |
An object created by |
trait.idx |
A vector giving the indices of traits to be analyzed. |
... |
not used. |
The function returns a data frame containing the multi-trait GWAS results, where the row names are
the variants names. The column names are: variant name (Marker
), allele frequency (Freq
),
the smallest sample size of the traits (N
), effect on the phenotype score (Beta.S
, see reference),
standard error (SE
), p-value (P
), and the rest the coefficients to construct the phenotype score
(see reference).
Either gwaa.data
(for GenABEL data format) or the combination of
phenofile
and genofile
(for DatABEL data format) has to be provided.
If all are provided, only phenofile
and genofile
will be used. When using
DatABEL format input, individual IDs in phenofile
and genofile
have to match!
Xia Shen
Shen X, Klaric L, Sharapov S, Mangino M, Ning Z, Wu D, Trbojevic-Akmacic I, Pucic-Bakovic M, Rudan I, Polasek O, Hayward C, Spector TD, Wilson JF, Lauc G, Aulchenko YS (2017): Multivariate discovery and replication of five novel loci associated with Immunoglobulin G N-glycosylation. Nature Communications, 8, 447; doi: 10.1038/s41467-017-00453-3.
## Not run: ## loading example gwaa.data in GenABEL require(GenABEL) data(ge03d2ex.clean) ## running multivariate GWAS for 3 traits: height, weight, bmi loaded <- MultiLoad(gwaa.data = ge03d2ex.clean, trait.cols = c(5, 6, 8), covariate.cols = c(2, 3)) ## running the multivariate GWAS res <- Multivariate(loaded) ## End(Not run)