parallelnewhybrid

"Parallelnewhybrid" is a software tool designed to identify hybrid individuals and quantify the uncertainty surrounding the identifications. Hybridization is a crucial aspect of many areas in biology, and the study of hybridization has direct applicability to testing hypotheses about evolution, speciation, genetic recombination, and having conservation, legal, and regulatory implications. However, identifying hybrid individuals and quantifying the uncertainty surrounding the identifications remains difficult.

Unlike other programs that exist to identify hybrids based on genotypic information, "newhybrids" is able to assign individuals to specific hybrid classes (e.g., F1, F2) because it makes use of patterns of gene inheritance within each locus rather than just the proportions of gene inheritance within each individual. It is essential to use multiple independent runs of each data set to develop an estimate of the hybrid class assignment accuracy for each comparison and set of markers.

The necessity of analyzing multiple simulated data sets constructed from large genomewide data sets presents significant computational challenges. To address these challenges, the authors present an R package called "parallelnewhybrid." This package is designed to decrease user burden when undertaking multiple newhybrids analyses. "Parallelnewhybrid" takes advantage of the parallel computational capabilities inherent in modern computers to efficiently and automatically execute separate newhybrids runs in parallel.

The package affords users several-fold reductions in time over a traditional serial analysis. "Parallelnewhybrid" consists of an example data set, a readme, and three operating system-specific functions to execute parallel newhybrids analyses on each computer's c cores. It is freely available on the long-term software hosting site GitHub, making it accessible to users.