hlaPublish {HIBAG} | R Documentation

## Finalize a HIBAG model

### Description

Finalize a HIBAG model by removing unused SNP predictors and adding appendix information (platform, training set, authors, warning, etc)

### Usage

    hlaPublish(mobj, platform=NULL, information=NULL, warning=NULL,
        rm.unused.snp=TRUE, anonymize=TRUE, verbose=TRUE)

### Arguments

`mobj` | an object of `hlaAttrBagObj` or `hlaAttrBagClass`
`platform` | the text of platform information
`information` | the other information, like authors
`warning` | any warning message
`rm.unused.snp` | if `TRUE`, remove unused SNPs from the model
`anonymize` | if `TRUE`, remove sample IDs
`verbose` | if TRUE, show information

### Value

Returns a new object of `hlaAttrBagObj`.

### Author(s)

Xiuwen Zheng

### See Also

`hlaModelFromObj`, `hlaModelToObj`

### Examples

    # make a "hlaAlleleClass" object
    hla.id <- "A"
    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 <- 250   # 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 a HIBAG model
    #
    set.seed(1000)

    # please use "nclassifier=100" when you use HIBAG for real data
    model <- hlaAttrBagging(hla, train.geno, nclassifier=2, verbose.detail=TRUE)
    summary(model)
    length(model$snp.id)

    mobj <- hlaPublish(model,
        platform = "Illumina 1M Duo",
        information = "Training set -- HapMap Phase II")
    model2 <- hlaModelFromObj(mobj)
    length(mobj$snp.id)
    mobj$appendix
    summary(mobj)

    p1 <- predict(model, train.geno)
    p2 <- predict(model2, train.geno)

    # check
    cbind(p1$value, p2$value)

[Package HIBAG version 1.22.0 Index]