Abstract
Abstract
Molecular properties of human diseases and conditions often exhibit dependence on the genetic ancestry of the donor. In order to make more human molecular data available for ancestry-informed research, we developed a set of software tools termed Robust Ancestry Inference using Data Synthesis (RAIDS) for inference of genetic ancestry from sequence data that pose challenges to genotyping. Here we describe a recent expansion and refinement of RAIDS, applicable to nucleic-acid sequence data resultant from a broad range of experimental strategies. These strategies currently include whole-genome, whole-exome, and targeted gene panel sequencing, RNA-Seq, including single-cell RNA-Seq, chromatin-accessibility (ATAC-Seq), and protein-binding (ChIP-Seq) assays. RAIDS inferential tools perform robustly in the presence of somatic nucleic-acid alterations caused by cancer and under the conditions of extreme non-uniformity of sequence read coverage, yielding both global ancestry and ancestral admixtures of the donor. RAIDS is available as an eponymous Bioconductor package.