related: an R package for analysing pairwise relatedness from codominant molecular markers

Abstract

Analyses of pairwise relatedness represent a key component to addressing many topics in biology. However, such analyses have been limited because most available programs provide a means to estimate relatedness based on only a single estimator, making comparison across estimators difficult. Second, all programs to date have been platform specific, working only on a specific operating system. This has the undesirable outcome of making choice of relatedness estimator limited by operating system preference, rather than being based on scientific rationale. Here, we present a new R package, called related, that can calculate relatedness based on seven estimators, can account for genotyping errors, missing data and inbreeding, and can estimate 95% confidence intervals. Moreover, simulation functions are provided that allow for easy comparison of the performance of different estimators and for analyses of how much resolution to expect from a given data set. Because this package works in R, it is platform independent. Combined, this functionality should allow for more appropriate analyses and interpretation of pairwise relatedness and will also allow for the integration of relatedness data into larger R workflows.

Social benefits of non-kin food sharing by female vampire bats

“…We measured two basic forms of social network centrality: the number of bats that have fed a subject ('indegree') and the number of bats that a subject has fed ('outdegree'). We estimated relatedness using the R package 'related' [18] from genotypes of 19 polymorphic microsatellite markers (see the electronic supplementary material for details). We define 'non-kin' as partners with a pairwise relatedness estimate of zero or less.…”

Genetic mating system and mate selection in smallmouth bass

“…We estimated pairwise genetic relatedness (R; Queller & Goodnight, 1989) between all male–female spawning pairs using the package RELATED v1.0 (Pew, Muir, Wang, & Frasier, 2015) in R (R Development Core Team, 2016) to investigate female mate choice and determine whether females actively avoided mating with close relatives or pursued additional spawning partners to whom they were less related than the first male with which they spawned (based on nest phenology data). A relatedness score of −1 represents two maximally dissimilar individuals, a score of 1 indicates individuals having identical genotypes, and a score of zero represents the average relatedness of two randomly chosen individuals in the population.…”

Genetic population structure and relatedness in the narrow‐striped mongoose (Mungotictis decemlineata), a socialMalagasy carnivore with sexual segregation

“…2006; Pew et al. 2015). In order to select the best relatedness estimator based on our data, we used the R package related (Pew et al.…”

“…In order to select the best relatedness estimator based on our data, we used the R package related (Pew et al. 2015). This package implements the functionality of COANCESTRY (Wang 2011), but it also allows for an explicit comparisons across seven different relatedness estimators, five moment estimators (Queller and Goodnight 1989; Li et al.…”

“…To determine whether individuals within categories were more closely related than expected, we compared the observed values for each category against a distribution of “expected” relatedness values generated by randomly shuffling individuals between categories groups for 1000 permutations and keeping size constant using the R package related (Pew et al. 2015). If the observed mean relatedness was greater than that of the permuted data ( P  >   0.95), then the null hypothesis, that the mean within‐category relatedness is random, was rejected.…”