bioRxiv2023
Background and ObjectiveGenetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. Recombination rates vary across the human genome and cannot be automatically derived from linkage physical maps. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, the only existing implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns, we developed Recombulator-X, a new open-source Python tool. MethodsThe most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm, coupled with JIT compilation to further increase performance. We also extended the statistical framework from STR to any polymorphic marker. ResultsCompared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. ConclusionsIn the genetic forensic community, state-of-the-art estimation methods for X chromosome recombination rates have seen limited usage due to the technical hurdles posed by previous implementations. Recombulator-X makes the process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices. Moreover, it extends the estimation framework to larger panels of genetic markers (not only STRs), allowing analyses of sequencing-based data.