tidypopgen (version 0.4.3)

windows_stats_generic: Estimate window statistics from per locus estimates

Description

This function is mostly designed for developers: it is a general function to estimate window statistics from per locus estimates. This function takes a vector of per locus estimates, and aggregates them by sum or mean per window. To compute specific quantities directly from a gen_tibble, use the appropriate window_* functions, e.g windows_pairwise_pop_fst() to compute pairwise Fst.

Usage

windows_stats_generic(
  .x,
  loci_table,
  operator = c("mean", "sum", "custom"),
  window_size,
  step_size,
  size_unit = c("snp", "bp"),
  min_loci = 1,
  complete = FALSE,
  f = NULL,
  ...
)

Value

A tibble with columns: 'chromosome', 'start', 'end', 'stats', and 'n_loci'. The 'stats' column contains the mean of the per locus estimates in the window, and 'n_loci' contains the number of loci in the window.

Arguments

.x

A vector containing the per locus estimates.

loci_table

a dataframe including at least a column 'chromosome', and additionally a column 'position' if size_unit is "bp".

operator

The operator to use for the window statistics. Either "mean", "sum" or "custom" to use a custom function .f.

window_size

The size of the window to use for the estimates.

step_size

The step size to use for the windows.

size_unit

Either "snp" or "bp". If "snp", the window size and step size are in number of SNPs. If "bp", the window size and step size are in base pairs.

min_loci

The minimum number of loci required to calculate a window statistic. If the number of loci in a window is less than this, the window statistic will be NA.

complete

Should the function be evaluated on complete windows only? If FALSE, the default, then partial computations will be allowed at the end of the chromosome.

f

a custom function to use for the window statistics. This function should take a vector of locus estimates and return a single value.

...

Additional arguments to be passed to the custom operator function.

Examples

example_gt <- load_example_gt("gen_tbl")

miss_by_locus <- loci_missingness(example_gt)

# Calculate mean missingness across windows
windows_stats_generic(miss_by_locus,
  loci_table = show_loci(example_gt),
  operator = "mean", window_size = 1000,
  step_size = 1000, size_unit = "bp",
  min_loci = 1, complete = FALSE
)