hlaModelFiles: Load a model object from files

In HIBAG: HIBAG -- HLA Genotype Imputation with Attribute Bagging

Description

To load HIBAG models from a list of files, and merge all together.

Usage

hlaModelFiles(fn.list, action.missingfile=c("ignore", "stop"), verbose=TRUE)

Arguments

fn.list	a vector of file names
action.missingfile	"ignore", ignore the missing files, by default; "stop", stop if missing
verbose	if TRUE, show information

Value

Return hlaAttrBagObj.

Author(s)

Xiuwen Zheng

See Also

hlaAttrBagging, hlaModelToObj

Examples

# load HLA types and SNP genotypes
data(HLA_Type_Table, package="HIBAG")
data(HapMap_CEU_Geno, package="HIBAG")

# make a "hlaAlleleClass" object
hla.id <- "C"
hla <- hlaAllele(HLA_Type_Table$sample.id,
	H1 = HLA_Type_Table[, paste(hla.id, ".1", sep="")],
	H2 = HLA_Type_Table[, paste(hla.id, ".2", sep="")],
	locus=hla.id, assembly="hg19")

# training genotypes
region <- 100   # kb
snpid <- hlaFlankingSNP(HapMap_CEU_Geno$snp.id, HapMap_CEU_Geno$snp.position,
	hla.id, region*1000, assembly="hg19")
train.geno <- hlaGenoSubset(HapMap_CEU_Geno,
	snp.sel = match(snpid, HapMap_CEU_Geno$snp.id),
	samp.sel = match(hla$value$sample.id, HapMap_CEU_Geno$sample.id))

#
# train HIBAG models
#
set.seed(1000)

# please use "nclassifier=100" when you use HIBAG for real data
model1 <- hlaAttrBagging(hla, train.geno, nclassifier=1, verbose.detail=TRUE)
mobj1 <- hlaModelToObj(model1)
save(mobj1, file="tm1.RData")

model2 <- hlaAttrBagging(hla, train.geno, nclassifier=1, verbose.detail=TRUE)
mobj2 <- hlaModelToObj(model2)
save(mobj2, file="tm2.RData")

model3 <- hlaAttrBagging(hla, train.geno, nclassifier=1, verbose.detail=TRUE)
mobj3 <- hlaModelToObj(model3)
save(mobj3, file="tm3.RData")

# load all of mobj1, mobj2 and mobj3
mobj <- hlaModelFiles(c("tm1.RData", "tm2.RData", "tm3.RData"))
summary(mobj)

HIBAG documentation built on May 2, 2019, 4:50 p.m.