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Kaitlin Samocha

Publications and source records attributed to Kaitlin Samocha.

3 recordsLinked to original sources

Refining the role of de novo protein truncating variants in neurodevelopmental disorders using population reference samples

Recent research has uncovered an important role for de novo variation in neurodevelopmental disorders. Using aggregated data from 9246 families with autism spectrum disorder, intellectual disability, or developmental delay, we show ~1/3 of de novo variants are independently observed as standing variation in the Exome Aggregation Consortiums cohort of 60,706 adults, and these de novo variants do not contribute to neurodevelopmental risk. We further use a loss-of-function (LoF)-intolerance metric, pLI, to identify a subset of LoF-intolerant genes that contain the observed signal of associated de novo protein truncating variants (PTVs) in neurodevelopmental disorders. LoF-intolerant genes also carry a modest excess of inherited PTVs; though the strongest de novo impacted genes contribute little to this, suggesting the excess of inherited risk resides lower-penetrant genes. These findings illustrate the importance of population-based reference cohorts for the interpretation of candidate pathogenic variants, even for analyses of complex diseases and de novo variation.

Genetics

Quantifying the unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects

Introduction Introduction Results Discussion 1. Preliminaries 2.1 Performance Guarantees 2. The UnseenEst Algorithm 3. Datasets 4. Validation experiments 5. Related works 6.1 Faithful samples 6.2 Chebyshev construction 6.3 Proof of Proposition... 6. Proofs of the... References References Recent efforts aggregating the genomes and exomes of tens of thousands of individuals have provided unprecedented insights into the landscape of rare human genetic variation1,2 and generated critical resources for clinical and population genetics. The recently announced U.S. Precision Med ...

Genetics

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). The resulting catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We show that this catalogue can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 72% of which have no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human \"knockout\" variants in protein-coding genes.

Genomics