Package 'snpAIMeR'

Title: Assess the Diagnostic Power of Genomic Marker Combinations
Description: Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.
Authors: Kim Vertacnik [cre, aut] , Oksana Vernygora [aut] , Julian Dupuis [aut]
Maintainer: Kim Vertacnik <[email protected]>
License: MIT + file LICENSE
Version: 2.1.1
Built: 2025-02-15 04:41:08 UTC
Source: https://github.com/cran/snpAIMeR

Help Index

Assess the Diagnostic Power of Genomic Marker Combinations

Description

Population genetics package for optimizing diagnostic panels. User-selected candidate markers are assessed individually and in combination for how well they can predict the source population of known samples. Requires a genotype file in STRUCTURE format.

Usage

snpAIMeR(run_mode, config_file = NULL, verbose = TRUE)

Arguments

run_mode

Modes are "interactive", "non-interactive", or "example"; mode must be in quotes.
config_file

Yaml file required for "non-interactive" mode; filename/path must be in quotes.
verbose

Default is TRUE.

Details

Yaml file format for "non-interactive" mode (do not include bullet points):

  • min_range: <minimum panel size>

  • max_range: <maximum panel size; we recommend no more than 15 markers>

  • assignment_rate_threshold: <value from 0 to 1>

  • cross_validation_replicates: <we recommend 100 minimum>

  • working_directory: <path name in quotes>

  • structure_file: <path name in quotes>

  • number_of_individuals: <same as adegenet's "n.ind">

  • number_of_loci: <same as adegenet's "n.loc">

  • one_data_row_per_individual: <TRUE or FALSE>

  • column_sample_IDs: <column number>

  • column_population_assignments: <column number>

  • column_other_info: <column number>

  • row_markernames: <row number>

  • no_genotype_character: <default is "-9">

  • optional_population_info: <optional>

  • genotype_character_separator: <optional>

Minimizing run time: Because of the number of possible combinations, we recommend testing no more than 15 markers. For example, testing 15 markers in panel sizes of 1 to 15 (32,767 total combinations) with 1,000 cross-validation replicates on a system with 48 processor cores took about 5 hours and 20 GB RAM. Reducing the number of cross-validation replicates will reduce run time, however, we recommend no less than 100 replicates.

Value

Cross-validation assignment rates for individual markers, marker combinations, and panel sizes. Outputs three .csv and two .pdf files to a user-specified directory.

See Also

https://github.com/OksanaVe/snpAIMeR

Examples

if (requireNamespace("adegenet", quietly = TRUE)) {
  data(nancycats, package = "adegenet")
  snpAIMeR("example", verbose = TRUE)
}