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Yi-Hui Zhou

Bio: Yi-Hui Zhou is an academic researcher from North Carolina State University. The author has contributed to research in topics: Medicine & Genome-wide association study. The author has an hindex of 25, co-authored 69 publications receiving 6424 citations. Previous affiliations of Yi-Hui Zhou include University of North Carolina at Chapel Hill.


Papers
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Journal ArticleDOI
Kristin G. Ardlie, David S. DeLuca, Ayellet V. Segrè, Timothy J. Sullivan, Taylor Young, Ellen Gelfand, Casandra A. Trowbridge, Julian Maller, Taru Tukiainen, Monkol Lek, Lucas D. Ward, Pouya Kheradpour, Benjamin Iriarte, Yan Meng, Cameron D. Palmer, Tõnu Esko, Wendy Winckler, Joel N. Hirschhorn, Manolis Kellis, Daniel G. MacArthur, Gad Getz, Andrey A. Shabalin, Gen Li, Yi-Hui Zhou, Andrew B. Nobel, Ivan Rusyn, Fred A. Wright, Tuuli Lappalainen, Pedro G. Ferreira, Halit Ongen, Manuel A. Rivas, Alexis Battle, Sara Mostafavi, Jean Monlong, Michael Sammeth, Marta Melé, Ferran Reverter, Jakob M. Goldmann, Daphne Koller, Roderic Guigó, Mark I. McCarthy, Emmanouil T. Dermitzakis, Eric R. Gamazon, Hae Kyung Im, Anuar Konkashbaev, Dan L. Nicolae, Nancy J. Cox, Timothée Flutre, Xiaoquan Wen, Matthew Stephens, Jonathan K. Pritchard, Zhidong Tu, Bin Zhang, Tao Huang, Quan Long, Luan Lin, Jialiang Yang, Jun Zhu, Jun Liu, Amanda Brown, Bernadette Mestichelli, Denee Tidwell, Edmund Lo, Mike Salvatore, Saboor Shad, Jeffrey A. Thomas, John T. Lonsdale, Michael T. Moser, Bryan Gillard, Ellen Karasik, Kimberly Ramsey, Christopher Choi, Barbara A. Foster, John Syron, Johnell Fleming, Harold Magazine, Rick Hasz, Gary Walters, Jason Bridge, Mark Miklos, Susan L. Sullivan, Laura Barker, Heather M. Traino, Maghboeba Mosavel, Laura A. Siminoff, Dana R. Valley, Daniel C. Rohrer, Scott D. Jewell, Philip A. Branton, Leslie H. Sobin, Mary Barcus, Liqun Qi, Jeffrey McLean, Pushpa Hariharan, Ki Sung Um, Shenpei Wu, David Tabor, Charles Shive, Anna M. Smith, Stephen A. Buia, Anita H. Undale, Karna Robinson, Nancy Roche, Kimberly M. Valentino, Angela Britton, Robin Burges, Debra Bradbury, Kenneth W. Hambright, John Seleski, Greg E. Korzeniewski, Kenyon Erickson, Yvonne Marcus, Jorge Tejada, Mehran Taherian, Chunrong Lu, Margaret J. Basile, Deborah C. Mash, Simona Volpi, Jeffery P. Struewing, Gary F. Temple, Joy T. Boyer, Deborah Colantuoni, Roger Little, Susan E. Koester, Latarsha J. Carithers, Helen M. Moore, Ping Guan, Carolyn C. Compton, Sherilyn Sawyer, Joanne P. Demchok, Jimmie B. Vaught, Chana A. Rabiner, Nicole C. Lockhart 
08 May 2015-Science
TL;DR: The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
Abstract: Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysi...

4,418 citations

Journal ArticleDOI
TL;DR: A mathematical expression is derived to compute PrediXcan results using summary data, and the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes are investigated.
Abstract: Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.

657 citations

Journal ArticleDOI
TL;DR: Gen expression profiles in 2,752 twins were assessed, using a classic twin design, to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood, providing a new resource toward understanding the genetic control of transcription.
Abstract: We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

385 citations

Journal ArticleDOI
TL;DR: DNA methylation beta value with concurrent body mass index (BMI) and waist circumference (WC), and BMI change, adjusting for batch effects and potential confounders was tested in the Atherosclerosis Risk in Communities study.
Abstract: Obesity is an important component of the pathophysiology of chronic diseases. Identifying epigenetic modifications associated with elevated adiposity, including DNA methylation variation, may point to genomic pathways that are dysregulated in numerous conditions. The Illumina 450K Bead Chip array was used to assay DNA methylation in leukocyte DNA obtained from 2097 African American adults in the Atherosclerosis Risk in Communities (ARIC) study. Mixed-effects regression models were used to test the association of methylation beta value with concurrent body mass index (BMI) and waist circumference (WC), and BMI change, adjusting for batch effects and potential confounders. Replication using whole-blood DNA from 2377 White adults in the Framingham Heart Study and CD4+ T cell DNA from 991 Whites in the Genetics of Lipid Lowering Drugs and Diet Network Study was followed by testing using adipose tissue DNA from 648 women in the Multiple Tissue Human Expression Resource cohort. Seventy-six BMI-related probes, 164 WC-related probes and 8 BMI change-related probes passed the threshold for significance in ARIC (P < 1 × 10(-7); Bonferroni), including probes in the recently reported HIF3A, CPT1A and ABCG1 regions. Replication using blood DNA was achieved for 37 BMI probes and 1 additional WC probe. Sixteen of these also replicated in adipose tissue, including 15 novel methylation findings near genes involved in lipid metabolism, immune response/cytokine signaling and other diverse pathways, including LGALS3BP, KDM2B, PBX1 and BBS2, among others. Adiposity traits are associated with DNA methylation at numerous CpG sites that replicate across studies despite variation in tissue type, ethnicity and analytic approaches.

280 citations

Journal ArticleDOI
TL;DR: This paper used genome-wide association analysis to identify genetic modifiers of CF lung disease, the primary cause of mortality, and provided new insights into potential targets for modulating lung disease severity in CF.
Abstract: The identification of small molecules that target specific CFTR variants has ushered in a new era of treatment for cystic fibrosis (CF), yet optimal, individualized treatment of CF will require identification and targeting of disease modifiers. Here we use genome-wide association analysis to identify genetic modifiers of CF lung disease, the primary cause of mortality. Meta-analysis of 6,365 CF patients identifies five loci that display significant association with variation in lung disease. Regions on chr3q29 (MUC4/MUC20; P=3.3 × 10(-11)), chr5p15.3 (SLC9A3; P=6.8 × 10(-12)), chr6p21.3 (HLA Class II; P=1.2 × 10(-8)) and chrXq22-q23 (AGTR2/SLC6A14; P=1.8 × 10(-9)) contain genes of high biological relevance to CF pathophysiology. The fifth locus, on chr11p12-p13 (EHF/APIP; P=1.9 × 10(-10)), was previously shown to be associated with lung disease. These results provide new insights into potential targets for modulating lung disease severity in CF.

244 citations


Cited by
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Journal ArticleDOI
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html .

47,038 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Posted ContentDOI
17 Nov 2014-bioRxiv
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-Seq data, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data. DESeq2 uses shrinkage estimation for dispersions and fold changes to improve stability and interpretability of the estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression and facilitates downstream tasks such as gene ranking and visualization. DESeq2 is available as an R/Bioconductor package.

17,014 citations

Journal Article
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel1, Eric Vallabh Minikel2, Kaitlin E. Samocha, Eric Banks2, Timothy Fennell2, Anne H. O’Donnell-Luria3, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria2, James S. Ware, Andrew J. Hill4, Andrew J. Hill2, Andrew J. Hill1, Beryl B. Cummings1, Beryl B. Cummings2, Taru Tukiainen2, Taru Tukiainen1, Daniel P. Birnbaum2, Jack A. Kosmicki, Laramie E. Duncan1, Laramie E. Duncan2, Karol Estrada1, Karol Estrada2, Fengmei Zhao1, Fengmei Zhao2, James Zou2, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo2, Ron Do, Jason Flannick2, Jason Flannick1, Menachem Fromer, Laura D. Gauthier2, Jackie Goldstein2, Jackie Goldstein1, Namrata Gupta2, Daniel P. Howrigan2, Daniel P. Howrigan1, Adam Kiezun2, Mitja I. Kurki2, Mitja I. Kurki1, Ami Levy Moonshine2, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso2, Gina M. Peloso1, Ryan Poplin2, Manuel A. Rivas2, Valentin Ruano-Rubio2, Samuel A. Rose2, Douglas M. Ruderfer8, Khalid Shakir2, Peter D. Stenson6, Christine Stevens2, Brett Thomas2, Brett Thomas1, Grace Tiao2, María Teresa Tusié-Luna, Ben Weisburd2, Hong-Hee Won9, Dongmei Yu, David Altshuler2, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly2, Roberto Elosua, Jose C. Florez2, Jose C. Florez1, Stacey Gabriel2, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll2, Steven A. McCarroll1, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale2, Benjamin M. Neale1, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan21, Patrick F. Sullivan14, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins16, Hugh Watkins17, James G. Wilson24, Mark J. Daly2, Mark J. Daly1, Daniel G. MacArthur1, Daniel G. MacArthur2 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: 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) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This 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 have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having 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.

8,758 citations