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cff-version: 1.2.0
message: 'To cite package "paneljudge" in publications use:'
type: software
license: MIT
title: 'paneljudge: Judge the performance of a panel of genetic markers using simulated
  data'
version: 0.0.0.9000
abstract: An R package to judge the performance of a panel of genetic markers using
  data simulated for pairs of haploid genotypes. The data are simulated under a hidden
  Markov model of relatedness (described in Taylor, A.R., Jacob, P.E., Neafsey, D.E.
  and Buckee, C.O., 2019. Estimating relatedness between malaria parasites. Genetics,
  212(4), pp.1337-1351) using allele frequency estimates provided by the user and
  inter-marker distances. The markers are treated as categorical random variables
  whose realisations (alleles) are unordered. The effective cardinalities and diversities
  of the markers can be computed using the input allele frequency estimates. Panel
  performance can be judged in terms of the root mean square error (RMSE) and confidence
  interval width of estimated relatedness, where relatedness is estimated under the
  same model used to simulate the data. At present, the examples we provide do not
  consider model misspecification; do not account for uncertainty around input allele
  frequency estimates; do not consider relatedness between pairs of haploid genotypes
  simulated using different allele frequencies; do not account for marker drop-out
  (markers that fail to produce useful data, e.g. because they a monomorphic). Otherwise
  stated, in the examples provided, the performance of a panel is judged in its most
  favourable light; it will likely perform less well in reality.
authors:
- family-names: Taylor
  given-names: Aimee
  email: ataylor@hsph.harvard.edu
  orcid: https://orcid.org/0000-0002-2337-8992
- family-names: Jacob
  given-names: Pierre
  orcid: https://orcid.org/0000-0002-3126-6966
repository: https://plasmogenepi.r-universe.dev
contact:
- family-names: Taylor
  given-names: Aimee
  email: ataylor@hsph.harvard.edu
  orcid: https://orcid.org/0000-0002-2337-8992