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Intro to meta-analysis of GWASs
 
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Raymond Walters, Massachusetts General Hospital & Broad Institute of MIT and Harvard gives a lecture on: Introduction to meta-analysis of genome-wide association studies (GWAS)
Views: 322 Dennis Lal
Meta-analysis of genome-wide association studies
 
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Ευάγγελος Ευαγγέλου, Επίκουρος Καθηγητής στον Τομέα Υγιεινής και Επιδημιολογίας της Ιατρικής Σχολής του Πανεπιστημίου Ιωαννίνων. http://www.compgen.org/intdamus/
Views: 114 Panagiota Kontou
Genome-Wide Association Studies - Karen Mohlke (2012)
 
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March 14, 2012 - Current Topics in Genome Analysis 2012 More: http://www.genome.gov/COURSE2012
BroadE: Statistical Genetics - Meta-analysis
 
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Copyright Broad Institute, 2013. All rights reserved. BroadE: Statistical Genetics - Meta-analysis - Daniel Howrigan These presentations were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Website: http://www.broadinstitute.org/partnerships/education/broade/broade-statistical-genetics About Broad Workshops BroadE workshops bring researchers in the extended Broad community together so they can learn from one another. BroadE workshops (the 'E' stands for education) offer insights and share hands-on training in breakthrough technologies, high-throughput methods, and computational tools not typically found in conventional research labs. Through this ongoing series, which is open to Broad staff and to researchers at MIT, Harvard and Harvard-affiliated hospitals, the Broad community hopes to extend the impact of its science and openly share new methods. Website: http://www.broadinstitute.org/partnerships/education/broade/broad-workshops
Views: 2047 Broad Institute
MPG Primer: Genome-wide association studies: QC, analysis, and interpretation (2012)
 
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Copyright Broad Institute, 2013. All rights reserved. The Primer on Medical and Population Genetics is a series of informal weekly discussions of basic genetics topics that relate to human populations and disease. Experts from across the Broad Institute community give in-depth introductions to the basic principles of complex trait genetics, including human genetic variation, genotyping, DNA sequencing methods, statistics, data analysis, and more. Videos of these sessions are made freely available for viewing here and are geared toward a wide audience that includes research technicians, graduate students, postdoctoral fellows and established investigators just entering the field. For more information, please visit: -Program in Medical Population Genetics (http://www.broadinstitute.org/node/224/) -Primer videos (http://www.broadinstitute.org/node/1339/)
Views: 12589 Broad Institute
GWAS
 
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Views: 105 Agriculture
Genome-Wide SNP Association
 
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The following short tutorial covers an abbreviated SNP analysis workflow on a whole-genome scale in SVS 7.
Views: 6236 Golden Helix Inc.
New method turns the tables on genome-wide studies
 
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New research in Nature Biotechnology, led by Josh Denny, M.D., M.S., associate professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center, exploits repurposed genetic data and electronic medical records to accomplish the first large-scale phenome-wide association study, or PheWAS. http://news.vanderbilt.edu/2013/12/first-large-scale-phewas-study-using-emrs-provides-systematic-method-to-discover-new-disease-associations/
Views: 1134 Vanderbilt University
Rare Cancer Meta-Analysis, pt4.1: Review and introduction to heat maps and clustering
 
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This entry is part four in a series of instructional videos detailing a meta-analysis on eight different human gene expression studies looking at papillary renal cell carcinoma (pRCC). In these installments, I use Partek Genomics Suite to display the meta-data as a heat map and employ hierarchical clustering to find connected genes in the dataset based on its normalized gene scores across all 17 different comparisons. A text file containing the papillary meta-analysis used in this video can be accessed at this Google Drive link: https://drive.google.com/file/d/1BgeoWMUl-B9JW99o4xrKt6kdUFiG7iEc/view?usp=sharing Inspiration for this meta-analysis on papillary kidney cancer came from an upcoming ‘Hackathon’ in May (https://sv.ai/papillary-renal-cell-carcinoma/) that brings together researchers, engineers and computer scientists to try to tackle challenging problems in life sciences. This year they are focusing on papillary renal-cell carcinoma type 1 (p1RCC), a disease that accounts for between 15 to 20% of all kidney cancers. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist. The opinions expressed during this video are mine and may not represent the opinions of the companies associated with the bioinformatics tools I use in these videos. Any uses of the products described in this demonstration may be uses that have not been cleared or approved by the FDA or any other applicable regulatory body. I do not get direct compensation from the platforms I demonstrate in these videos, but do receive reimbursement for travel when I speak at company-sponsored events. Please subscribe to this YouTube channel or sign up to my blog (www.bioinfosolutions.com/blog/) to receive notifications on when the next video in the series is posted. Special thanks goes out to the biotech companies Illumina (Correlation Engine and Cohort Analyzer), Partek Inc. (Partek Genomics Suite) and Elsevier (Pathway Studio) for donating their platforms and providing technical assistance for this bioinformatics series.
Views: 51 Michael Edwards
Effect size calculation and basic meta-analysis, David B. Wilson
 
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David Wilson delivers a crash course in meta-analysis. This workshop presentation was recorded in Washington at the Campbell Colloquium 2011. Find out more about the work of the Campbell Collaboration today: https://www.campbellcollaboration.org/ See also David's popular meta-analysis effect size calculator here: https://www.campbellcollaboration.org/research-resources/research-for-resources/effect-size-calculator.html
Neuroimaging, Genetics & Meta-Analysis: Discussing ENIGMAtters with ENIGMA Director Paul Thompson
 
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Enhancing Neuro Imaging Genetics Through Meta Analysis: In Episode 4 of the Discussing ENIGMAtters web series, Paul Thompson, PhD, talks about how the ENIGMA Consortium came to be, and what fuels it today. With interesting insights on imaging genetics, Dr. Thompson provides an overview of the culture and how to keep it moving forward by collaborating with geneticists, radiologists, mathematicians, psychiatrists and physicians from all over the world. To learn more about the ENIGMA Consortium, visit http://enigma.ini.usc.edu/, follow us on Twitter (https://twitter.com/enigmabrains), or like us on Facebook (https://www.facebook.com/EnigmaBrain/).
Views: 313 ENIGMA Consortium
BroadE: Statistical Genetics - Population stratification
 
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Copyright Broad Institute, 2013. All rights reserved. BroadE: Statistical Genetics: Population stratification - Taru Tukiainen These presentations were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Website: http://www.broadinstitute.org/partnerships/education/broade/broade-statistical-genetics About Broad Workshops BroadE workshops bring researchers in the extended Broad community together so they can learn from one another. BroadE workshops (the 'E' stands for education) offer insights and share hands-on training in breakthrough technologies, high-throughput methods, and computational tools not typically found in conventional research labs. Through this ongoing series, which is open to Broad staff and to researchers at MIT, Harvard and Harvard-affiliated hospitals, the Broad community hopes to extend the impact of its science and openly share new methods. Website: http://www.broadinstitute.org/partnerships/education/broade/broad-workshops
Views: 3238 Broad Institute
BroadE: Statistical Genetics - Plink and QC and Practical
 
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Copyright Broad Institute, 2013. All rights reserved. BroadE: Statistical Genetics: Plink and QC and Practical - Verneri Anttila These presentations were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Website: http://www.broadinstitute.org/partnerships/education/broade/broade-statistical-genetics About Broad Workshops BroadE workshops bring researchers in the extended Broad community together so they can learn from one another. BroadE workshops (the 'E' stands for education) offer insights and share hands-on training in breakthrough technologies, high-throughput methods, and computational tools not typically found in conventional research labs. Through this ongoing series, which is open to Broad staff and to researchers at MIT, Harvard and Harvard-affiliated hospitals, the Broad community hopes to extend the impact of its science and openly share new methods. Website: http://www.broadinstitute.org/partnerships/education/broade/broad-workshops
Views: 14402 Broad Institute
GWAS Association Analysis - module 1
 
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Visit the course registration page at https://www.soph.uab.edu/ssg/statgenetics/onlineedu/videoseries Visit GWAS Association Analysis course content resource for more hands-on instructions : https://www.soph.uab.edu/ssg/statgenetics/onlineedu/videoseries/amit
Views: 198 Stat Genetics
MPG Primer: GWAS and secondary analyses of GWAS results (2018)
 
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November 29, 2018 MPG Primer: GWAS and secondary analyses of GWAS results Gina Peloso Department of Biostatistics Boston University School of Public Health The Primer on Medical and Population Genetics is a series of informal weekly discussions of basic genetics topics that relate to human populations and disease. Experts from across the Broad Institute community give in-depth introductions to the basic principles of complex trait genetics, including human genetic variation, genotyping, DNA sequencing methods, statistics, data analysis, and more. Videos of these sessions are made freely available for viewing here and are geared toward a wide audience that includes research technicians, graduate students, postdoctoral fellows, and established investigators just entering the field. For more information, please visit: -Program in Medical Population Genetics (http://www.broadinstitute.org/node/224/) -Primer videos (http://www.broadinstitute.org/node/1339/) Copyright Broad Institute, 2018. All rights reserved.
Views: 514 Broad Institute
5D - Genome-wide association studies
 
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5d_full This is Lecture 5D of the free online course Useful Genetics Part 1. All of the lectures are on YouTube in the Useful Genetics library. Register for the full course here: https://www.edx.org/course/useful-genetics-part-1-how-genes-shape-ubcx-usegen-1x
Views: 3843 Useful Genetics
MPG Primer: Genome-wide association studies: past and present (2014)
 
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Copyright Broad Institute, 2014. All rights reserved. MPG Primer: Genome-wide association studies: past and present Alisa Manning - Altshuler Lab, Broad Institute The Primer on Medical and Population Genetics is a series of informal weekly discussions of basic genetics topics that relate to human populations and disease. Experts from across the Broad Institute community give in-depth introductions to the basic principles of complex trait genetics, including human genetic variation, genotyping, DNA sequencing methods, statistics, data analysis, and more. Videos of these sessions are made freely available for viewing here and are geared toward a wide audience that includes research technicians, graduate students, postdoctoral fellows, and established investigators just entering the field.
Views: 728 Broad Institute
BroadE: Statistical Genetics - Association testing
 
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Copyright Broad Institute, 2014. All rights reserved. The presentations below were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis.
Views: 2609 Broad Institute
BroadE: Statistical Genetics - Introduction to the biometrical model and GWAS technology
 
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Copyright Broad Institute, 2013. All rights reserved. BroadE: Statistical Genetics: Introduction to the biometrical model and GWAS technology - Benjamin Neale These presentations were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Website: http://www.broadinstitute.org/partnerships/education/broade/broade-statistical-genetics About Broad Workshops BroadE workshops bring researchers in the extended Broad community together so they can learn from one another. BroadE workshops (the 'E' stands for education) offer insights and share hands-on training in breakthrough technologies, high-throughput methods, and computational tools not typically found in conventional research labs. Through this ongoing series, which is open to Broad staff and to researchers at MIT, Harvard and Harvard-affiliated hospitals, the Broad community hopes to extend the impact of its science and openly share new methods. Website: http://www.broadinstitute.org/partnerships/education/broade/broad-workshops
Views: 4750 Broad Institute
Webcast- A walk through GWAS
 
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Genome-wide association studies (GWAS) have been providing valuable insight to the genetics of common and complex diseases for many years. In this webcast we will walk through one possible workflow for completing GWAS in Golden Helix SNP & Variation Suite (SVS) with special attention paid to adjusting analysis for population stratification. The webcast will include: • Visualizations including Manhattan Plots, linkage disequilibrium plots, and genomic annotation sources. • Quality assurance including cryptic relatedness, population stratification, as well as sample and marker statistics. • Genotype association tests and statistics including Corr/Trend tests, logistic and linear regression, Mixed Linear Models, and more
Views: 7632 Golden Helix Inc.
Single Trait GWAS Analysis Tutorial  SOLAR eclipse software
 
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Single Trait GWAS Analysis Tutorial SOLAR eclipse software Links to commands: http://solar-eclipse-genetics.org/solar-commands.html This video was made in the lab of Dr. Peter Kochunov, at the Maryland Psychiatric Research Center (MPRC). You can access his website at http://solar-eclipse-genetics.org.
Views: 145 Fatima Talib
Across-cohort QC analyses of GWAS summary statistics from complex traits
 
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Chen et al. propose four metrics for large-scale genome-wide association meta-analysis. I) It can verify the genetic origin of each cohort; II) it can identify significant sample overlap or heterogeneity between pairs of cohorts; III) it can deep clean overlapping samples without reveal individual-level data. Read the full article here: http://dx.doi.org/10.1038/ejhg.2016.106
Views: 7 EJHG Tube
Genetics Update - InterLymph 2017
 
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Susan Slager, PhD, Mayo Clinic, Rochester, Minnesota InterLymph Genetics Working Group The InterLymph Consortium ( International Consortium of Investigators Working on Lymphoma Epidemiologic Studies) is an international group of scientists who undertake research projects and pool data across studies to better understand lymphoma risk factors. https://epi.grants.cancer.gov/InterLymph Visit http://www.lymphomacoalition.org to get up to date facts and statistics about lymphoma. Links to publications: http://www.mayo.edu/research/searchpublications/publications?authid=11288183 Chronic Lymphocytic Leukemia: Prevalence, Outcomes, and Pathological Findings. https://www.ncbi.nlm.nih.gov/pubmed/28940587?dopt=Abstract Relationship between co-morbidities at diagnosis, survival and ultimate cause of death in patients with chronic lymphocytic leukaemia (CLL): a prospective cohort study. https://www.ncbi.nlm.nih.gov/pubmed/28580636?dopt=Abstract Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia. https://www.ncbi.nlm.nih.gov/pubmed/28165464?dopt=Abstract Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia. https://www.ncbi.nlm.nih.gov/pubmed/26956414?dopt=Abstract Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types. https://www.ncbi.nlm.nih.gov/pubmed/26464424?dopt=Abstract
Views: 68 Lymphoma Coalition
Do Your Genes Make You FAT? | Is there a FAT gene?
 
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The first 300 people to click this link will get 2 months of Skillshare for free: ▹ https://skl.sh/buttermore6 ▹Skillshare is an online learning community for creators with over 22,000 courses videography, business, photography, and more! ___________________ Women's Specialization Program ▹ ▹https://www.stephaniebuttermore.com/womens-specialization-program Link For FREE SAMPLE (WEEK1) ▹https://www.stephaniebuttermore.com/about/ Please Subscribe! http://bit.ly/substephaniebuttermore Follow me on Instagram! ▹ @stephanie_buttermore ___________________ Scale I Use: ▹ Body Analyzer 60% off code [sbuttermore] link: http://vpwow.com/sbuttermore -Tracks weight, body fat, muscle mass bone density and water weight. Supplements I Use: 15% off All Pescience Products CODE: STEPH http://bit.ly/stephpescience ------------------------------- Recommended Videos▹ ▹EP. 4 Does Birth Control Make you Fat? ▹https://youtu.be/2e5Lh8jtEX8 ------------------------------- REFERENCES▹ ▹The Women’s Book by Lyle McDonald w/ Eric Helms http://bit.ly/StephBodyRecomposition ▹Loos & Yeo (2014): “ The Bigger Picture of FTO – the first GWAS-identified obesity gene’ ▹Frayling et al. (2007): “A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity” ▹Speakman (2015): “The ‘Fat Mass and Obesity Related’ (FTO) gene: Mechanisms of Impact on Obesity and Energy Balance” ▹Li et al. (2010): “Cumulative effects and predictive value of common obesity-susceptibility variants identified by genome-wide association studies” ▹Livingstone (2016): “FTO genotype and weight loss: systematic review and meta-analysis of 9563 individual participant data from eight randomised controlled trials” ▹Kalantari et al. (2016): “Review of studies on the fat mass and obesity-associated (FTO) gene interactions with environmental factors affecting on obesity and its impact on lifestyle interventions” ▹Quan et al. (2015): “Association of fat-mass and obesity-associated gene FTO rs9939609 polymorphism with the risk of obesity among children and adolescents: a meta-analysis” ▹TER da Silva (2018): “The FTO rs9939609 polymorphism and obesity risk in teens: Evidence-based meta-analysis” ------------------------------- FOLLOW ME ▹ INSTAGRAM ‣ http://instagram.com/stephanie_buttermore SNAPCHAT ‣ http://snapchat.com/add/steph_butter FACEBOOK ‣ http://facebook.com/stephaniebuttermore JEFF'S INSTAGRAM ‣ http://instagram.com/jeffnippard JEFF'S CHANNEL ‣ https://www.youtube.com/jeffnippard ------------------------------- CONTACT ME ▹ BUSINESS ONLY EMAIL: [email protected] ------------------------------- FAQs ▹ 1.What is your ethnicity? ‣ Mom is Thai and Dad is Canadian..Eh? 2. How tall are you? ‣ 5'4" 3. How old are you? ‣ 28 3. What are you researching? ‣ Watch my PhD Day in the life video ▹ http://bit.ly/dayasaphd 4. Is Jeff my boyfriend? ‣ Duh 5. Is that your real hair? ‣ Yes ___ AYOOO!! My name is Stephanie Buttermore and in a few words I am a fitness enthusiast but a scientist at heart! Just obtained my Ph.D. in pathology and cell biology with a research focus on the molecular mechanisms that drive ovarian cancer progression. Hope you stick around! xoxo
Views: 100853 Stephanie Buttermore
MIA: Hilary Finucane, Identifying disease related cell types from GWAS data
 
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October 4, 2017 Hilary Finucane Broad Fellow Insight into the biology of common diseases using summary statistics of large genome-wide association studies Abstract: Data from genome-wide association studies (GWAS) contain valuable information about the genetic basis of the disease. For most common diseases, obtaining insights from these data is difficult because the signal is very diffuse: there are likely thousands or tens of thousands of causal variants, each with a very small effect size on disease risk. Moreover, for many of the largest disease GWAS, no individual researcher has access to all of the genotype data; rather, the only data available are meta-analyzed marginal effect size estimates for each variant. I will describe a powerful approach to modeling these summary statistics that allows us, for example, to identify disease-relevant tissues and cell types, or to quantify the degree to which two traits have a common genetic basis. The approach, called LD score regression, is based on a commonly used model in genetics in which the effect size of each variant on the disease is random. The parameters of this model provide information about the disease such as whether regions of the genome active in a given tissue (e.g., liver) tend to be more associated with disease than regions of the genome active in a second tissue (e.g., brain). I will present results from an application of LD score regression to identify relevant tissues and cell types from several large GWAS, and from an application of LD score regression to identify pairs of phenotypes with shared genetic basis. Associated papers: 1) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495769/ 2) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626285/ 3) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797329/ 4) https://www.biorxiv.org/content/early/2017/09/15/103069 For more information on the Broad Institute and Models, Inference and Algorithms visit: https://www.broadinstitute.org/mia Copyright Broad Institute, 2017. All rights reserved.
Views: 1465 Broad Institute
Predicting and Meta-Analysis
 
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We are excited to announce and demonstrate some new and highly requested features in this webcast, including predicting phenotypes by applying existing GBLUP or Bayesian models and meta-analysis for GWAS studies.
Views: 284 Golden Helix Inc.
MPG Primer: GWAS and secondary analyses of GWAS results (2017)
 
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September 28th, 2017 MPG Primer: GWAS and secondary analyses of GWAS results Gina Peloso Broad Institute Boston University School of Public Health MPG Primer: The Primer on Medical and Population Genetics is a series of informal weekly discussions of basic genetics topics that relate to human populations and disease. Experts from across the Broad Institute community give in-depth introductions to the basic principles of complex trait genetics, including human genetic variation, genotyping, DNA sequencing methods, statistics, data analysis, and more. Videos of these sessions are made freely available for viewing here and are geared toward a wide audience that includes research technicians, graduate students, postdoctoral fellows, and established investigators just entering the field. If you'd like more information about the primers visit: https://www.broadinstitute.org/scientific-community/science/programs/medical-and-population-genetics/primers/primer-medical-and-pop Copyright Broad Institute, 2017. All rights reserved.
Views: 2040 Broad Institute
BroadE: Statistical Genetics - Rare variants
 
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Copyright Broad Institute, 2013. All rights reserved. BroadE: Statistical Genetics - Rare variants - Kaitlin E. Samocha These presentations were filmed during the September 2013 Statistical Genetics Workshop, part of the BroadE Workshop series. This workshop provides an introduction to the basic principles of statistical genetic analysis. This course is targeted for individuals who are interested in learning the basics of genetic analysis. Specific areas of focus for the course include: study design considerations for genetic association tests, quality control (QC) procedures for genetic data, basic analysis of genome-wide association SNP data, and introduction to rare variant testing approaches. The workshop blended lectures introducing each of these topics and then hands-on practical application, in particular for QC and common variant analysis. Website: http://www.broadinstitute.org/partnerships/education/broade/broade-statistical-genetics About Broad Workshops BroadE workshops bring researchers in the extended Broad community together so they can learn from one another. BroadE workshops (the 'E' stands for education) offer insights and share hands-on training in breakthrough technologies, high-throughput methods, and computational tools not typically found in conventional research labs. Through this ongoing series, which is open to Broad staff and to researchers at MIT, Harvard and Harvard-affiliated hospitals, the Broad community hopes to extend the impact of its science and openly share new methods. Website: http://www.broadinstitute.org/partnerships/education/broade/broad-workshops
Views: 4114 Broad Institute
Tutorial of GWAS data analysis
 
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Walk through pulling and analyzing GWAS LD blocks
Views: 82 MolecularScience
Robert Roberts - Genetics of Coronary Artery Disease
 
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Watch on LabRoots at: http://labroots.com/user/webinars/details/id/42 Susceptibility to coronary artery disease (CAD) is claimed to be 40% to 60% inherited, but until recently genetic risk factors predisposing to CAD have been elusive. Comprehensive prevention of CAD requires manipulation of genetic risk. The availability of microarrays of single-nucleotide polymorphisms enabling genome-wide association studies (GWAS) led to the discovery of 50 genetic risk variants for CAD. Surprisingly, 35 risk variants mediate their risk through unknown mechanisms, with only 17 associating with hypertension or lipids. Thus, there are several mechanisms contributing to the pathogenesis of CAD yet to be elucidated. The first risk variant discovered by GWAS was 9p21.3, which occurs in 75% of all populations except African, with a mean increased risk of 25% per copy. Of the 50 variants for CAD, the increased risk varies from 6% to 92% with a mean increased risk of 18%, occurring on average in 47% of the population. The maximum number of risk alleles per individual would be 100. In the CARDIoGRAM (Coronary Artery Disease Genome-wide Replication and Meta Analysis) study of 23 variants, the average per individual was 17, the minimum 7, and the maximum 37. The top 10th percentile has an odds ratio of 1.88 and the lowest percentile an odds ratio of 0.55. Routine genetic screening is unlikely until management is improved by genetic testing. Risk variants should provide pathophysiological insights and targets for novel therapy. While risk variants are less potent predictors of CAD, compared with biomarkers, they have the advantage of not changing in one's lifetime and are unaffected by diet, sex, age, or medication.
Views: 672 LabRoots
GWA-Portal Tutorial
 
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A simple walkthrough of the main features of the GWA-Portal. https://gwas.gmi.oeaw.ac.at/ 0:00 - 3:00 GWAS Wizard (Upload phenotypes and create a GWA study) 3:00 - 6:30 Manhattan Plots (Interpret GWAS results) 6:30 - end Meta-Analysis (Discover pleiotropic effects, analyze your favorite gene or accession)
How to sequence the human genome - Mark J. Kiel
 
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View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence. Lesson by Mark J. Kiel, animation by Marc Christoforidis.
Views: 570339 TED-Ed
Blame Migraines On Your Parents
 
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Migraines suck. And according to new research, that terrible, debilitating pain might be one more thing you can blame on your parents. Read More: Genome-wide Meta-Analysis Identifies New Susceptibility Loci For Migraine http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.2676.html "Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls." Genetic roots of migraine uncovered http://www.kcl.ac.uk/newsevents/news/newsrecords/2013/06-June/Genetic-roots-of-migraine-uncovered.aspx "In the largest ever study of migraines, researchers have found five genetic regions that for the first time have been linked to the onset of migraine." Oxidative stress in Parkinson's disease http://onlinelibrary.wiley.com/doi/10.1002/ana.10483/abstract "Oxidative stress contributes to the cascade leading to dopamine cell degeneration in Parkinson's disease (PD). However, oxidative stress is intimately linked to other components of the degenerative process, such as mitochondrial dysfunction, excitotoxicity, nitric oxide toxicity and inflammation." Watch More: Lightning Causes Headaches: http://www.youtube.com/watch?v=hqvPeC7N3zQ Brain Freeze!: http://www.youtube.com/watch?v=JTCVcc3Fmp0 Distort: Shattering Roses: http://www.youtube.com/watch?v=-gvxOBfHiE4 ____________________ DNews is dedicated to satisfying your curiosity and to bringing you mind-bending stories & perspectives you won't find anywhere else! New videos twice daily. Watch More DNews on TestTube http://testtube.com/dnews Subscribe now! http://www.youtube.com/subscription_center?add_user=dnewschannel DNews on Twitter http://twitter.com/dnews Anthony Carboni on Twitter http://twitter.com/acarboni Laci Green on Twitter http://twitter.com/gogreen18 Trace Dominguez on Twitter http://twitter.com/trace501 DNews on Facebook http://facebook.com/dnews DNews on Google+ http://gplus.to/dnews Discovery News http://discoverynews.com
Views: 29931 Seeker
MIA: Christina Chen, PCA and stratification in GWAS; Alex Bloemendal, primer on random matrix theory
 
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Models, Inference and Algorithms Broad Institute of MIT and Harvard March 13, 2019 MIA Meeting: https://youtu.be/B7ub92OLw1g?t=3493&list=PLlMMtlgw6qNjROoMNTBQjAcdx53kV50cS Alex Bloemendal Neale Lab A primer on random matrix theory Abstract: High-dimensional data behave in ways that seem to contradict intuitions from low-dimensional geometry and classical statistics, particularly in testing for and recovering low rank signal. Random matrix theory is a branch of mathematics that characterizes such phenomena; I will sketch a few relevant results. Christina Chen Neale Lab Controlling for stratification in (meta)-GWAS with PCA: theory, applications, and implications Abstract: Principal component analysis (PCA) is the standard method for estimating population structure and sample ancestry in genetic datasets. Population structure can induce confounding in genome-wide association studies (GWAS), which is typically addressed by including principal components (PCs) as covariates. However, results from random matrix theory (RMT) predict that PCA fails to detect population differentiation below a particular threshold and that even above the threshold, sample PCs may be only partially correlated with true axes of differentiation. These phenomena depend for each PC on the corresponding eigenvalue; we extend previous work to characterize and interpret the eigenvalues for general population structures. Moreover, we propose an estimator for the effective number of unlinked variants that outperforms previous moments-based estimators, which we then combine with RMT results to estimate the inaccuracy of each PC and predict how this inaccuracy leads to residual confounding in GWAS on stratified phenotypes. We validate our method via downsampling experiments on real data including the UK Biobank and suggest this behavior may be driving the uncorrected stratification recently observed in some large meta-analyses of smaller GWAS. For more information on the Broad Institute and Models, Inference and Algorithms visit: https://www.broadinstitute.org/mia Copyright Broad Institute, 2019. All rights reserved.
Views: 341 Broad Institute
GWAS associations, 2005-2017
 
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GWAS associations, 2005-2017 Genome-wide association studies (GWAS) have produced thousands of genetic regions associated to common diseases and traits, since the first small GWAS were performed in 2005, followed by large-scale efforts starting in 2007. Conducted by researchers at the Broad Institute and other institutions around the globe, these studies have shed light on the biological underpinnings of many common diseases, including schizophrenia, inflammatory bowel disease, and type 2 diabetes. Diagrams showing GWAS associations across the genome are courtesy of the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas) Reference: MacArthur J, et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). [https://www.ebi.ac.uk/gwas] Nucleic Acids Research, 2017, Vol. 45 (Database issue): D896-D901. For more coverage of the first decade of GWAS, see the Broad Institute website (https://www.broadinstitute.org/node/67471). Copyright Broad Institute, 2017. All rights reserved.
Views: 2592 Broad Institute
David Balding - Heritability-based models for prediction of complex traits
 
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MLPM Summerschool 2015 Monday 21st of September Heritability-based models for prediction of complex traits by David Balding Complex trait genetics has been revolutionised over the past 5 years by developments related to the concept of heritability. Heritability is the fraction of phenotypic variation that can be attributed to genetic mechanisms (mostly we focus on narrow-sense heritability, which considers only additive genetic effects). Since we cannot identify and measure the causal genetic mechanisms, a traditional approach has been to use pedigree relatedness as a proxy for the sharing of causal alleles between individuals. Pedigree relatedness even came to be seen as central to the concept of heritability, which perhaps explains why it was not until 2010 that it became widely appreciated that genome-wide genetic markers (SNPs) offered at least a "noisy" way to directly measure causal alleles, and hence a new approach to assessing heritability. This approach is "noisy" because SNPs generally only tag causal variants imperfectly, depending on SNP density and linkage disequilibrium, and many SNPs may tag little or no causal variation. So genome-wide SNP-based heritability estimates are difficult to interpret, but they can provide a lower bound which was enough to show that SNPs usually tag much more causal variation than can be attributed to genome-wide significant SNPs. Another big step forward has been that heritability can be attributed to different genes, genomic regions or functional classes, and for many phenotypes it is found to be widely dispersed across the genome, with relatively little concentration in coding regions. Further, heritability has become a unit of common currency for gene-based tests and meta-analysis. I will review the ideas and the underlying mathematical models, and present some recent results.
Genome-Wide Association Studies for the Rest of Us: Final Panel Discussion
 
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Genome-Wide Association Studies for the Rest of Us: Adding Genome-Wide Association to Population Studies Panel Members: Teri Manolio, M.D., Ph.D., Jim Ostell, Ph.D., Nancy Cox, Ph.D., Wendy Post, M.D., David Hunter, M.B.B.S., M.P.H., Sc.D., Robert Hoover, M.D., Sc.D., Laura Scott, Ph.D. and Marta Gwinn, M.D., M.P.H. http://www.genome.gov/25522004
Farhad Hormozdiari: "Fine mapping and post-GWAS Era"
 
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July 28, 2016 presentation at UCLA for CGSI 2016
Views: 730 ZarlabUCLA
Medical Genetics of Addiction
 
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https://www.amazon.com/Medical-Genetics-Addiction-Garden-Grove/dp/1545161151 This article collection reviews the medical genetics of addiction and includes 23 papers by various authors. Topics include: Contribution of BDNF and DRD2 genetic polymorphisms to continued opioid use in patients receiving methadone treatment for opioid use disorder: an observational study; Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction; Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction; Case-control association analysis of Dopamine receptor polymorphisms in alcohol dependence: a pilot study in Indian males; Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs; Schizophrenia and substance use comorbidity: a genome-wide perspective; The association between age of onset of opioid use and comorbidity among opioid dependent patients receiving methadone maintenance therapy; Genetic influences on nicotinic alpha5 receptor (CHRNA5) CpG methylation and mRNA expression in brain and adipose tissue; Genetics and epigenetics of alcohol dependence; Sex differences in substance use, health, and social functioning among opioid users receiving methadone treatment: a multicenter cohort study; Hippocampal changes produced by overexpression of the human CHRNA5/A3/B4 gene cluster may underlie cognitive deficits rescued by nicotine in transgenic mice; COMPULS: design of a multicenter phenotypic, cognitive, genetic, and magnetic resonance imaging study in children with compulsive syndromes; Genetic influence of dopamine receptor, dopamine transporter, and nicotine metabolism on smoking cessation and nicotine dependence in a Japanese population; A non-parametric approach for detecting gene-gene interactions associated with age-at-onset outcomes; Dopamine-beta hydroxylase polymorphism and cocaine addiction; Epidemiology, radiology, and genetics of nicotine dependence in COPD; Variation in the gene coding for the M5 Muscarinic receptor (CHRM5) influences cigarette dose but is not associated with dependence to drugs of addiction: evidence from a prospective population based cohort study of young adults; Association between Common Genetic Variants in the Opioid Pathway and Smoking Behaviors in Chinese Men; Relationship among methadone dose, polymorphisms of dopamine D2 receptor and tri-dimensional personality questionnaire in heroin-addicted patients; MeCP2 and the enigmatic organization of brain chromatin. Implications for depression and cocaine addiction; The Netrin-1 receptor DCC is a regulator of maladaptive responses to chronic morphine administration; Dopamine D2 receptor polymorphisms and susceptibility to alcohol dependence in Indian males: a preliminary study; Variation in regulator of G-protein signaling 17 gene (RGS17) is associated with multiple substance dependence diagnoses.
Views: 34 James Bonnar
Klotho polymorphisms and longevity: a systematic review - Calogero Caruso
 
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Nowadays is clearly evident that genetic background constitutes integral part of successful ageing and longevity. Many studies on long lived people have been conducted emphasizing the role of certain genes in long life. Classic case-control studies, genome wide association studies and high throughput sequencing have permitted to identify a variety of genetic variants seemingly associated to longevity. Over the years, ageing research has focused on insulin/IGF-1 signaling pathway because of its evolutionary conserved correlation with life-span extension in model animals. Indeed, many single nucleotide polymorphisms (SNPs), associated with longevity were identified in genes encoding proteins that take part in this metabolic pathway. Recently we have conducted a meta-analysis that has showed the association of IGF-1R and FOXO3A polymorphisms with longevity. Closely related to this pathway is the Klotho gene. It encodes a type-I membrane protein expressed primarily in the kidney in two forms, membrane and secreted. The last form acts suppressing oxidative stress and growth factor signalling and regulating ion channels and trasporters. Its overexpression seems to be able to suppress insulin/IGF-1 signaling extending life span as showed in transgenic mice. Thus, our aim is to put together the results showed in literature concerning the association between SNPs of Klotho and longevity to quantify the possible effect of each single SNP and its magnitude. The results of our systematic review indicate that Klotho SNPs are associated with ageing. Visit www.sens.org/videos to view the rest of our SENS6 videos.
Views: 1104 SENS Foundation
Functional consequences of intelligence GWAS loci from 87,740 individuals
 
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Jonathan Coleman, King's College London presents his BioRxiv paper: Functional consequences of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals Here is abstract & paper: https://www.biorxiv.org/content/early/2017/07/31/170712
Views: 196 Dennis Lal
Study Designs: Genetic Association Studies
 
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Teri Manolio, M.D., Ph.D. Director, Office of Population Genomics, NHGRI. Genetics for Epidemiologists: Applications of Human Genomics to Population Sciences, was a short course for investigators and trainees in the field of epidemiology and related population-based sciences. It was conducted by the National Human Genome Research Institute (NHGRI) on May 13-14, 2008 at Northwestern University in Chicago. The goal of Genetics for Epidemiologists (GFE) was to familiarize epidemiologists and population-based researchers with recent developments in the theory and methods of human genetics that might be applied to the study of the distribution, natural history and etiology of diseases in populations. The course consisted of eight one-hour lectures and focused on the interface between genetics and epidemiology. Emphasis was on the application of modern human genome analysis methodologies to studies of human populations through the design, conduct, analysis, and interpretation of studies which effectively answer the epidemiologic question of interest. GFE is co-sponsored by the Office of Population Genomics, NHGRI, and the Department of Preventive Medicine at Northwestern University's Feinberg School of Medicine. These videocasts are provided as an educational tool for epidemiologic investigators interested in learning more about applying genomics to their work. More: http://www.genome.gov/27026645
MIT CompBio Lecture 23 - Multi-Phenotype analyses
 
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MIT Computational Biology: Genomes, Networks, Evolution, Health Prof. Manolis Kellis http://compbio.mit.edu/6.047/ Fall 2018 Lecture 23 - Multi-phenotype analyses 1. Motivation of phenome-wide association studies - PheWAS-informed phenotyping, improved GWAS power, etc - Electronic health record (EHR) contain rich personalized information 2. Modeling multiple phenotypes in GWAS + epigenomics - Integration of multiple phenotypes in GWAS from Systems Genetics perspective (clustering approach) - Direct integration of multiple phenotypes by summary-based factored genetic model estimation 3. Epigenomics of PheWAS - Risk variants inference using epigenomic reference annotations - Using disease covariance to improve functional variants inference - Combining enrichment to improve causal pathway inference 4. Meta-phenotype inference and imputation - Models leveraging missing information and inferring missing mechanism - Modeling multimodal electronic health record data - Imputing missing EHR code and prioritizing patient disease risks Slides for Lecture 23: https://stellar.mit.edu/S/course/6/fa18/6.047/courseMaterial/topics/topic2/lectureNotes/Lecture22_PheWAS_MultiPhenotypeAssociations_MK/Lecture23_PheWAS_MultiPhenotypeAssociations.pdf
Views: 228 Manolis Kellis
Aging | Interview with Dr. Gil Atzmon
 
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Full text - http://bit.ly/2zLec7l Aging | Interview with Dr. Gil Atzmon from the Department of Medicine and Genetics at Albert Einstein College of Medicine, in the Bronx, NY 10461, USA as well as the Department of Human Biology, Faculty of Natural Science, at the University of Haifa, in Haifa, Israel talking about their featured cover paper for Volume 9 Issue 1"The complex genetics of gait speed: genome-wide meta-analysis approach" Twitter - http://bit.ly/2tU6XXD Facebook - http://bit.ly/2zK4amM Linkedin - http://bit.ly/2zIqME5 Pintrest - http://bit.ly/2i0KDX1 Reddit - http://bit.ly/2zK6jPm www.Aging-US.com
Views: 224 Aging
Hands On with SNP & Variation Suite - GWAS Analysis (Part 1)
 
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This recording is from a Hands On session using SVS for GWAS analysis at Mayo Clinic on June 11th. More info on SVS: http://www.goldenhelix.com/SNP_Variation/index.html
Views: 1507 Golden Helix Inc.
Medical Genetics of Asthma
 
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https://www.amazon.com/Medical-Genetics-Asthma-Garden-Grove/dp/1545180946 This article collection reviews the medical genetics of asthma and includes 22 papers by various authors. Topics include: Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population; Association of ADAM33 gene polymorphisms with adult allergic asthma and rhinitis in a Chinese Han population; Respiratory symptoms among infants at risk for asthma: association with surfactant protein A haplotypes; A functional polymorphism in the SPINK5 gene is associated with asthma in a Chinese Han Population; Association of genetic variants in chromosome 17q21 and adult-onset asthma in a Chinese Han population; Analyses of associations between three positionally cloned asthma candidate genes and asthma or asthma-related phenotypes in a Chinese population; A pooling-based genome-wide analysis identifies new potential candidate genes for atopy in the European Community Respiratory Health Survey (ECRHS); Mechanistic role of a disease-associated genetic variant within the ADAM33 asthma susceptibility gene; Association study between vitamin D receptor gene polymorphisms and asthma in the chinese han population: a case-control study; Evaluation of the toll-like receptor 6 Ser249Pro polymorphism in patients with asthma, atopic dermatitis and chronic obstructive pulmonary disease; Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers; Asthma: Gln27Glu and Arg16Gly polymorphisms of the beta2-adrenergic receptor gene as risk factors; Effects of endotoxin exposure on childhood asthma risk are modified by a genetic polymorphism in ACAA1; Comprehensive genetic assessment of a functional TLR9 promoter polymorphism: no replicable association with asthma or asthma-related phenotypes; Leukotriene B4 receptor locus gene characterisation and association studies in asthma; Vitamin D binding protein variants associate with asthma susceptibility in the Chinese han population; Investigating highly replicated asthma genes as candidate genes for allergic rhinitis; Association of CD14 -260 (-159) C T and asthma: a systematic review and meta-analysis; The effect of CD14 and TLR4 gene polimorphisms on asthma phenotypes in adult Turkish asthma patients: a genetic study; Genome-wide association study identifies PERLD1 as asthma candidate gene; Large scale genotyping study for asthma in the Japanese population; ITGB5 and AGFG1 variants are associated with severity of airway responsiveness.
Views: 77 James Bonnar
Genome-Wide Association Studies (2010)
 
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March 09, 2010. Karen Mohlke, Ph.D. Current Topics in Genome Analysis 2010 Handout: http://www.genome.gov/Pages/Research/IntramuralResearch/DIRCalendar/CurrentTopicsinGenomeAnalysis2010/CTGA2010_Lec08_color.pdf More: http://www.genome.gov/12514286
USC Polygenic Conference - Session 2: New GWAS and Polygenic Scores I
 
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This is the second session in USC CESR's Polygenic Prediction and its Application in Social Science Conference, featuring presentations by Robbee Wedow and Meghan Zacher.
GWAS and prior knowledge to uncover gene-gene interactions
 
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- Marylyn Ritchie, Pennsylvania State University On Thursday, 18 July 2013, the NHGRI's Division of Genomic Medicine presented "Current uses of and future directions for the GWAS Catalog", a webinar highlighting current uses and exploring future directions for the GWAS catalog. These presentations from the webinar examine how the catalogue's use by biomedical researchers is informing projects such as ENCODE, mouse phenotyping projects and regulatory genomics. GWAS catalog personnel identify goals and directions for their work.
ASCPT 2019 Presidential Trainee - Guang Yang, MS
 
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AN INTERNATIONAL GENOME-WIDE META-ANALYSIS OF BISPHOSPHONATE RELATED OSTEONECROSIS OF THE JAW University of Florida, Gainesville, FL
Views: 16 ASCPT Alexandria