batchTest {GWASTools} | R Documentation

## Batch Effects of Genotyping

### Description

`batchChisqTest` calculates Chi-square values for batches from 2-by-2 tables of SNPs, comparing each batch with the other batches. `batchFisherTest` calculates Fisher's exact test values.

### Usage

    batchChisqTest(genoData, batchVar, snp.include = NULL,
                   chrom.include = 1:22, sex.include = c("M", "F"),
                   scan.exclude = NULL, return.by.snp = FALSE,
                   correct = TRUE, verbose = TRUE)

    batchFisherTest(genoData, batchVar, snp.include = NULL,
                    chrom.include = 1:22, sex.include = c("M", "F"),
                    scan.exclude = NULL, return.by.snp = FALSE,
                    conf.int = FALSE, verbose = TRUE)

### Arguments

`genoData` | `GenotypeData` object
`batchVar` | A character string indicating which annotation variable should be used as the batch.
`snp.include` | A vector containing the IDs of SNPs to include.
`chrom.include` | Integer vector with codes for chromosomes to include. Ignored if `snp.include` is not `NULL`. Default is 1:22 (autosomes). Use 23, 24, 25, 26, 27 for X, XY, Y, M, Unmapped respectively
`sex.include` | Character vector with sex to include. Default is c("M", "F"). If sex chromosomes are present in `chrom.include`, only one sex is allowed.
`scan.exclude` | A vector containing the IDs of scans to be excluded.
`return.by.snp` | Logical value to indicate whether snp-by-batch matrices should be returned.
`conf.int` | Logical value to indicate if a confidence interval should be computed.
`correct` | Logical value to specify whether to apply the Yates continuity correction.
`verbose` | Logical value specifying whether to show progress information.

### Details

Because of potential batch effects due to sample processing and genotype calling, batches are an important experimental design factor.

`batchChisqTest` calculates the Chi square values from 2-by-2 table for each SNP, comparing each batch with the other batches.

`batchFisherTest` calculates Fisher's Exact Test from 2-by-2 table for each SNP, comparing each batch with the other batches.

For each SNP and each batch, batch effect is evaluated by a 2-by-2 table: # of A alleles, and # of B alleles in the batch, versus # of A alleles, and # of B alleles in the other batches. Monomorphic SNPs are set to `NA` for all batches.

The default behavior is to combine allele frequencies from males and females and return results for autosomes only. If results for sex chromosomes (X or Y) are desired, use `chrom.include` with values 23 and/or 25 and `sex.include`="M" or "F".

If there are only two batches, the calculation is only performed once and the values for each batch will be identical.

### Value

`batchChisqTest` returns a list with the following elements:

`mean.chisq` | a vector of mean chi-squared values for each batch.
`lambda` | a vector of genomic inflation factor computed as `median(chisq) / 0.456` for each batch.
`chisq` | a matrix of chi-squared values with SNPs as rows and batches as columns. Only returned if `return.by.snp=TRUE`.

`batchFisherTest` returns a list with the following elements:

`mean.or` | a vector of mean odds-ratio values for each batch. `mean.or` is computed as `1/mean(pmin(or, 1/or))` since the odds ratio is >1 when the batch has a higher allele frequency than the other batches and <1 for the reverse.
`lambda` | a vector of genomic inflation factor computed as `median(-2*log(pval) / 1.39` for each batch.

Each of the following is a matrix with SNPs as rows and batches as columns, and is only returned if `return.by.snp=TRUE`:

`pval` | P value
`oddsratio` | Odds ratio
`confint.low` | Low value of the confidence interval for the odds ratio. Only returned if `conf.int=TRUE`.
`confint.high` | High value of the confidence interval for the odds ratio. Only returned if `conf.int=TRUE`.

`batchChisqTest` and `batchFisherTest` both also return the following if `return.by.snp=TRUE`:

`allele.counts` | matrix with total number of A and B alleles over all batches.
`min.exp.freq` | matrix of minimum expected allele frequency with SNPs as rows and batches as columns.

### Author(s)

Xiuwen Zheng, Stephanie Gogarten

### See Also

`GenotypeData`, `chisq.test`, `fisher.test`

### Examples

    library(GWASdata)
    file <- system.file("extdata", "illumina_geno.gds", package="GWASdata")
    gds <- GdsGenotypeReader(file)
    data(illuminaScanADF)
    genoData <-  GenotypeData(gds, scanAnnot=illuminaScanADF)

    # autosomes only, sexes combined (default)
    res.chisq <- batchChisqTest(genoData, batchVar="plate")
    res.chisq$mean.chisq
    res.chisq$lambda

    # X chromosome for females
    res.chisq <- batchChisqTest(genoData, batchVar="status",
      chrom.include=23, sex.include="F", return.by.snp=TRUE)
    head(res.chisq$chisq)

    # Fisher exact test of "status" on X chromosome for females
    res.fisher <- batchFisherTest(genoData, batchVar="status",
      chrom.include=23, sex.include="F", return.by.snp=TRUE)
    qqPlot(res.fisher$pval)

    close(genoData)

[Package GWASTools version 1.36.0 Index]