ImPoStAR: Implement Population Structure Analyses in R
The impostar package implements appropriate resampling strategies to model the total sampling error associated with either Sanger sequencing (population sampling error) or next-generation sequencing (population + sequencer sampling error) in two commonly applied statistical tests: (1) a binomial logistic regression test for a genetic cline and (2) the analysis of molecular variance (AMOVA) test for genetic structure. Accounting for the additional sequencer sampling error associated with next-generation sequencing is essential for controlling the level of false positive (‘impostar’) loci. For additional information, see: Hamner, R.M., J.D. Selwyn, E. Krell, S.A. King, and C.E. Bird. In review. Modeling next-generation sequencer sampling error in pooled population samples dramatically reduces false positives in genetic structure tests.