tidypopgen (version 0.4.3)

qc_report_indiv: Create a Quality Control report for individuals

Description

Return QC information to assess loci (Observed heterozygosity and missingness).

Usage

qc_report_indiv(.x, ...)
# S3 method for tbl_df
qc_report_indiv(.x, kings_threshold = NULL, ...)
# S3 method for grouped_df
qc_report_indiv(.x, kings_threshold = NULL, ...)

Value

If no kings_threshold is provided, a tibble with 2 elements: het_obs and missingness. If kings_threshold is provided, a tibble with 4 elements: het_obs, missingness, id and to_keep. For pseudohaploid data, a tibble with ploidy and missingness.

Arguments

.x

either a gen_tibble object or a grouped gen_tibble (as obtained by using dplyr::group_by())

...

further arguments to pass

kings_threshold

an optional numeric giving a KING kinship coefficient, or one of:

• "first": removing first degree relatives, equivalent to a kinship coefficient of 0.177 or more

• "second": removing second degree relatives, equivalent to a kinship coefficient of 0.088 or more

Details

Providing the parameter kings_threshold will return two additional columns, 'id' containing the ID of individuals, and 'to_keep' a logical vector describing whether the individual should be removed to retain the largest possible set of individuals with no relationships above the threshold. The calculated pairwise KING relationship matrix is also returned as an attribute of 'to_keep'. The kings_threshold parameter can be either a numeric KING kinship coefficient or a string of either "first" or "second", to remove any first degree or second degree relationships from the dataset. This second option is similar to using --unrelated --degree 1 or --unrelated --degree 2 in KING. For pseudohaploid data, only missingness and ploidy are reported.

Examples

# Create a gen_tibble of lobster genotypes
bed_file <-
  system.file("extdata", "lobster", "lobster.bed", package = "tidypopgen")
example_gt <- gen_tibble(bed_file,
  backingfile = tempfile("lobsters"),
  quiet = TRUE
)

# Get QC report for individuals
example_gt %>% qc_report_indiv()

# Get QC report with kinship filtering
example_gt %>% qc_report_indiv(kings_threshold = "first")