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Let's talk about sex: A rigorous statistical framework to assign the sex of individuals from reduced-representation sequencing data.

Jean-Sébastien MooreLaura Benestan
Published in: Molecular ecology resources (2019)
Molecular markers have been used to identify the sex of sampled individuals for several decades, but the time-consuming development phase prevented their application in many systems. Recently, a growing number of papers have applied reduced-representation sequencing (RRS) protocols to the identification of sex-specific markers without the use of test crosses or prior genomic information. While such an approach has great advantages in terms of versatility and ease of use, the "shotgun sequencing" nature of RRS data sets leads to a high amount of missing data, which results in statistical challenges to the confident assignment of sex to individuals. In this issue of Molecular Ecology Resources, Stovall et al. (Molecular Ecology Resources, 18, 2018) provide a statistical framework to answer two questions: (1) how many individuals of one sex only must possess a genotype for this locus to be considered significantly sex-specific? and (2) How many sex-specific loci must an individual of unknown sex possess (in a given data set) to be confidently assigned a sex? The statistical pipeline introduced, and applied to samples of New Zealand fur seal (Arctocephalus forsteri) to identify 90 sex-specific loci, should be broadly applicable to a large number of species and constitutes a nice addition to the molecular ecology toolkit in the genomics era.
Keyphrases
  • electronic health record
  • single cell
  • big data
  • healthcare
  • genome wide
  • gene expression
  • deep learning
  • bioinformatics analysis