HWETest {midasHLA} | R Documentation

## Test for Hardy Weinberg equilibrium

### Description

Test experiment features for Hardy Weinberg equilibrium.

### Usage

    HWETest(
      object,
      experiment = c("hla_alleles", "hla_aa", "hla_g_groups", "hla_supertypes",
        "hla_NK_ligands"),
      HWE_group = NULL,
      HWE_cutoff = NULL,
      as.MiDAS = FALSE
    )

### Arguments

`object` | `MiDAS` object.
`experiment` | String specifying experiment to test. Valid values includes `"hla_alleles"`, `"hla_aa"`, `"hla_g_groups"`, `"hla_supertypes"`, `"hla_NK_ligands"`.
`HWE_group` | Expression defining samples grouping to test for Hardy Weinberg equilibrium. By default samples are not grouped.
`HWE_cutoff` | Number specifying p-value threshold. When `HWE_group` is specified both groups are thresholded.
`as.MiDAS` | Logical flag indicating if MiDAS object should be returned.

### Details

Setting `as.MiDAS` to `TRUE` will filter MiDAS object based on p-value cut-off given by `HWE_cutoff`.

### Value

Data frame with Hardy Weinberg Equilibrium test results or a filtered MiDAS object.

### Examples

    # create MiDAS object
    midas <- prepareMiDAS(hla_calls = MiDAS_tut_HLA,
                          colData = MiDAS_tut_pheno,
                          experiment = "hla_alleles"
    )

    # get HWE p-values as data frame
    HWETest(midas, experiment = "hla_alleles")

    # get HWE in groups defined by disease status
    # grouping by `disease == 1` will divide samples into two groups:
    # `disease == 1` and `not disease == 1`
    HWETest(midas, experiment = "hla_alleles", HWE_group = disease == 1)

    # filter MiDAS object by HWE test p-value
    HWETest(midas, experiment = "hla_alleles", HWE_cutoff = 0.05, as.MiDAS = TRUE)

[Package midasHLA version 1.2.0 Index]