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Juan M. Peralta

Researcher at University of Texas at Austin

Publications -  93
Citations -  2610

Juan M. Peralta is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Genome-wide association study & Gene. The author has an hindex of 24, co-authored 78 publications receiving 1757 citations. Previous affiliations of Juan M. Peralta include University of Texas at Brownsville & Menzies Research Institute.

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Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Alexander G. Bick, +165 more
- 14 Oct 2020 - 
TL;DR: Analysis of high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine programme enables simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells.
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Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families.

TL;DR: This large-scale extended pedigree study of cognitive functioning in bipolar disorder identifies measures of processing speed, working memory, and declarative (facial) memory as candidate endophenotypes for bipolar disorder.
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Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

Madeline H. Kowalski, +86 more
- 23 Dec 2019 - 
TL;DR: It is demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data, which subsequently enhanced gene-mapping power for complex traits.
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Genetic Analysis Workshop 17 mini-exome simulation.

TL;DR: The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis.
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Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Xihao Li, +77 more
- 24 Aug 2020 - 
TL;DR: STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components and is scalable for analyzing large whole-genome sequencing studies.