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Filter SNP number per locus/read

Source: R/filter_snp_number.R
filter_snp_number.Rd

This filter removes outlier markers with too many SNP number per locus/read. The data requires snp and locus information (e.g. from a VCF file). Having a higher than "normal" SNP number is usually the results of assembly artifacts or bad assembly parameters. This filter is population-agnostic, but still requires a strata file if a vcf file is used as input.

Filter target: Markers.

Statistics: The number of SNPs per locus.

Usage

filter_snp_number(
  data,
  strata = NULL,
  interactive.filter = TRUE,
  filter.snp.number = NULL,
  filename = NULL,
  parallel.core = parallel::detectCores() - 1,
  verbose = TRUE,
  ...
)

Arguments

data

A tidy genomic data frame or another genomic object supported by the calling function.

strata

Optional strata file or object containing individual and group information. Default: strata = NULL.

interactive.filter

Logical indicating whether an interactive filtering session may display diagnostics and ask for thresholds. Default: interactive.filter = TRUE.

filter.snp.number

(integer) This is best decided after viewing the figures. If the argument is set to 2, locus with 3 and more SNPs will be blacklisted. Default: filter.snp.number = NULL.

filename

(optional) Name of the filtered tidy data frame file written to the working directory (ending with .tsv) Default: filename = NULL.

parallel.core

Number of workers available for parallel operations. Default: parallel.core = parallel::detectCores() - 1.

verbose

Logical. Display progress messages. Default: verbose = TRUE.

...

Additional arguments passed to lower-level screening or filtering functions.

Value

The filtered data in the same representation as the input. GDS marker metadata and active variants are updated in place. Diagnostic files, marker lists, and filtering parameters are written to the output folder.

Interactive version

The function first displays and writes the distribution of SNPs per locus and the effect of candidate thresholds. It then asks:

  1. "Do you still want to blacklist markers? (y/n):"

  2. If yes, choose 1 to use the upper boxplot-outlier statistic or 2 to enter a threshold.

  3. With option 2, answer "Enter the maximum number of SNP per locus allowed:".

All SNPs in loci containing more than the selected number are blacklisted. Answering no leaves the data unchanged. Use interactive.filter = FALSE and provide filter.snp.number explicitly for a reproducible analysis.

Examples

if (FALSE) { # \dontrun{
genome <- genometranslator::read_genome(
  data = "turtle.vcf",
  strata = "turtle.strata.tsv"
)

# Inspect the SNP-per-locus distribution interactively.
genome <- radr::filter_snp_number(data = genome)

# Alternatively, use a separate unfiltered GDS for a scripted run that
# retains loci containing at most four SNPs.
scripted_genome <- genometranslator::read_genome("turtle_scripted.gds")
scripted_genome <- radr::filter_snp_number(
  data = scripted_genome,
  interactive.filter = FALSE,
  filter.snp.number = 4
)
} # }