Skip to contents

Write a pcadapt file from a tidy data frame

Source: R/write_pcadapt.R
write_pcadapt.Rd

Write a pcadapt file from a tidy data frame. The data is biallelic. Used internally in genometranslator and might be of interest for users.

Prepare an appropriately filtered biallelic dataset before export. Consider missingness, minor-allele frequency, linkage disequilibrium, and the sampling design intended for the pcadapt analysis.

Usage

write_pcadapt(
  data,
  pop.select = NULL,
  filename = NULL,
  parallel.core = parallel::detectCores() - 1
)

Arguments

data

A tidy data frame object in the global environment or a tidy data frame in wide or long format in the working directory. How to get a tidy data frame ? Look into genometranslator tidy_genome.

pop.select

(optional, string) Selected list of populations for the analysis. e.g. pop.select = c("QUE", "ONT") to select QUE and ONT population samples (out of 20 pops). If pop.labels argument was used to rename the strata column, use the new names with pop.select. Default: pop.select = NULL.

filename

(optional) The file name prefix for the pcadapt file written to the working directory. With default: filename = NULL, the date and time is appended to radiator_pcadapt_. Default: filename = NULL.

parallel.core

Default: parallel.core = parallel::detectCores() - 1.

Value

A pcadapt file is written in the working directory a genotype matrix object is also generated in the global environment.

Details

Use a filtered dataset:

  1. Control linkage disequilibrium: Reducing linkage before running genome scan is essential. At least start by removing SNPs on the same RADseq locus (short linkage disequilibrium).

  2. Control minor alleles: Too much Minor Alleles is just noise in the data. Filter using Count, Frequency or Depth.

  3. Only use markers that are in common between strata

  4. Only use polymorphic markers

Data filtering

This writer does not silently filter markers or individuals. It may validate requirements imposed by the destination format and stop with an informative error when the input is unsuitable. It is the user's responsibility to filter and quality-control the data appropriately for the intended analysis before generating the output. Use radr or another suitable workflow when filtering is required.

Dependencies

Required package dependencies are declared in DESCRIPTION and are installed with genometranslator. Any additional dependency needed only for this format or option is identified in this help page. Use genometranslator_dependencies() to inspect the availability of core packages, optional packages, and external executables.

References

Luu, K., Bazin, E., & Blum, M. G. (2017). pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular Ecology Resources, 17(1), 67-77.

Duforet-Frebourg, N., Luu, K., Laval, G., Bazin, E., & Blum, M. G. (2015). Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data. Molecular biology and evolution, msv334.

Author

Thierry Gosselin thierrygosselin@icloud.com