plot_diagnostic: Basic diagnostic plots

In hemstrow/snpR: Whole-Genome Analysis Tools for Use with Single Nucleotide Polymorphism Data

Basic diagnostic plots

Description

Create a suite of basic diagnostic plots (FIS density, 1D SFS, maf density, PCA, to describe the condition of the data in a snpRdata object.

Usage

plot_diagnostic(
  x,
  facet = NULL,
  projection = floor(nsnps(x)/1.2),
  fold_sfs = TRUE,
  plots = c("fis", "maf", "pca", "missingness", "heho")
)

Arguments

x	snpRdata object
facet	character, default NULL. Categorical metadata variables by which to break up plots. Note that only one facet is allowed here. Missingness and the PCA will have individuals colored by the given sample facet. See Facets_in_snpR for more details.
projection	integer, default floor(nsnps(x)/1.2). A sample size to project the SFS to, in number of gene copies. Sizes too large will result in a SFS containing few or no SNPs.
fold_sfs	logical, default TRUE. Determines if the SFS should be folded or left polarized. If FALSE, snp metadata columns named "ref" and "anc" containing the identity of the derived and ancestral alleles, respectively, should be present for polarization to be meaningful.
plots	character vector, default all possible plots except for SFS. Plot options: fis: density of FIS scores for all loci within each facet level. sfs: Site Frequency Spectra for the entire dataset. maf: density of minor allele frequencies for all loci within each facet. pca: Principal Component Analysis results for the given facet. missingness: Proportion of missing alleles across each individual withing each facet. heho: expected vs. observed heterozygosity for each locus within each facet. Very high expected or observed heterozygosities for many loci can indicate genotyping issues.

Value

A named list of diagnostic ggplot2 plots.

Author(s)

William Hemstrom

Examples

## Not run: 
# missingness and pca colored by pop
plot_diagnostic(stickSNPs, "pop")

## End(Not run)

hemstrow/snpR documentation built on March 20, 2024, 7:03 a.m.