Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions.
View Article and Find Full Text PDFAs the last decade of human genomics research begins to bear the fruit of advancements in precision medicine, it is important to ensure that genomics' improvements in human health are distributed globally and equitably. An important step to ensuring health equity is to improve the human reference genome to capture global diversity by including a wide variety of alternative haplotypes, sequences that are not currently captured on the reference genome.We present a method that localizes 100 basepair (bp) long sequences extracted from short-read sequencing that can ultimately be used to identify what regions of the human genome non-reference sequences belong to.
View Article and Find Full Text PDFAutism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children. While noncoding genetic variation has been shown to play a major role in many complex disorders, the contribution of these regions to ASD susceptibility remains unclear. Genetic analyses of ASD typically use unaffected family members as controls; however, we hypothesize that this method does not effectively elevate variant signal in the noncoding region due to family members having subclinical phenotypes arising from common genetic mechanisms.
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