hlaReport {HIBAG} | R Documentation

## Format a report

### Description

Create a report for evaluating prediction accuracies.

### Usage

    hlaReport(object, export.fn="", type=c("txt", "tex", "html", "markdown"),
        header=TRUE)

### Arguments

`object` | an object returned by `hlaCompareAllele`
`export.fn` | a file name for output, or "" for `stdout`
`type` | `"txt"` – tab-delimited text format; `"tex"` – tex format using the 'longtable' package; `"html"` – html file
`header` | if `TRUE`, output the header of text file associated corresponding format

### Value

None.

### Author(s)

Xiuwen Zheng

### See Also

`hlaCompareAllele`

### 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")

    # divide HLA types randomly
    set.seed(100)
    hlatab <- hlaSplitAllele(hla, train.prop=0.5)
    names(hlatab)
    # "training"   "validation"
    summary(hlatab$training)
    summary(hlatab$validation)

    # SNP predictors within the flanking region on each side
    region <- 500   # kb
    snpid <- hlaFlankingSNP(HapMap_CEU_Geno$snp.id, HapMap_CEU_Geno$snp.position,
        hla.id, region*1000, assembly="hg19")
    length(snpid)  # 275

    # training and validation genotypes
    train.geno <- hlaGenoSubset(HapMap_CEU_Geno,
        snp.sel = match(snpid, HapMap_CEU_Geno$snp.id),
        samp.sel = match(hlatab$training$value$sample.id,
        HapMap_CEU_Geno$sample.id))
    test.geno <- hlaGenoSubset(HapMap_CEU_Geno,
        samp.sel=match(hlatab$validation$value$sample.id,
        HapMap_CEU_Geno$sample.id))

    # train a HIBAG model
    set.seed(100)
    # please use "nclassifier=100" when you use HIBAG for real data
    model <- hlaAttrBagging(hlatab$training, train.geno, nclassifier=4,
        verbose.detail=TRUE)
    summary(model)

    # validation
    pred <- predict(model, test.geno)
    # compare
    (comp <- hlaCompareAllele(hlatab$validation, pred, allele.limit=model,
        call.threshold=0))

    # report
    hlaReport(comp, type="txt")

    hlaReport(comp, type="tex")

    hlaReport(comp, type="html")

    hlaReport(comp, type="markdown")

[Package HIBAG version 1.16.0 Index]