Changes

An Advanced Gene Mapping course will be held in New York online from Monday through Friday , January 2725-3129, 20202021. The cost of the 5-day course is $100 for student, academic , and government researchers and $21,800 500 for researchers working in industry. This fee covers tuition and course -related expenses (handoutscloud computing, etc.) but not room and board.

The course emphasis is on analyzing sequence and other omics data to elucidate the genetic etiology of complex human disease traits. Topics will include: data quality control of sequence and other types of data; single variant and aggregate rare variant association analysis of whole-genome data (genotype, sequence, and imputed) for qualitative and quantitative traits (population and family-based data); controlling for population admixture and substructure; generalized linear mix models and linear mixed models; meta-analysis; sample size estimation and power calculations; detecting gene x gene and gene x environmental interactions; analysis of epigenomic data, e.g methylation , and chromatin; heritability estimation using variant and RNA-Seq data; analysis of RNA-Seq data; eQTL mapping; elucidating pleiotropy; functional prediction and variant annotation; estimation of polygenic risk scores; Mendelian randomization; mediation analysis; and fine mapping.''' '''As mandated by the NIH there will also be a special session on responsible conduct of research that will include sessions on conflict of interest, research ethics, data management (security) , and ethical use of human research subjects.

A variety of freely available software will be used to perform the practical exercises, due to differences in their functionality. PSEQ, SEQSpark, and VAT will be used to analyze sequence data to perform annotation, quality control, rare variant association analysis , and meta-analysis. FaST-LMM, EPACTs, and GCTA-MLMA , REGENIE will be implemented to analyze population- and family-based data by applying generalized linear mixed models (qualitative traits) and linear mixed models (quantitative traits). For rare variant association analysis of trio data , RV-TDT will be applied. MultiPhen (multivariate) and PLINK (univariate) will be contrasted in their ability to detect pleiotropy; Mediation analysis will be performed using R to aid in distinguishing between biological, mediated, and spurious pleiotropy. To make inferences on causality, Mendelian randomization will be performed using MR-base. Estimation of polygenic risk scores will be performed using LDpred. PAINTOR and FOCUS non-parametric shrinkage. SuSie will be used for fine mapping to aid in the detection of causal susceptibility variants. Heritability estimates will be performed using GCTA. For analysis of eQTLs, Matrix eQTL will be used. Analysis of imputed expression data will be performed by applying PrediXCan; To perform analytical and empirical power analysis for single and rare variant aggregate tests, a variety of tools will be used that includes the Armitage Power Tool and the SKAT R library will be used. Additionally, variant annotation will be performed with ANNOVAR as well as directly using a variety of functional prediction and conservation tools, e.g. CADD, GERP, MutationTaster, MutPred, Polyphen-2, and SIFT.

The instructors for the course are: Heather Cordell (University of Newcastle), Nancy Cox (Vanderbilt University), Andrew DeWan (Yale University), Suzanne Leal (The Rockefeller University & Columbia University), Bogdan Pasaniuc (UCLA), and  [http://www.fas.harvard.edu/~biophys/Shamil_Sunyaev.htm Shamil Sunyaev] (Harvard University) & Gao Wang (Columbia University). Judy Matuk (HRP Consulting Group) will lecture on ethics and the regulation of human subject research. A special guest lecture will be given by Jurg Ott (Rockefeller University).

==More Additional Information==The maximum number of participants for this online course is 34.  The course will take place in the Great Hall in Welch at The Rockefeller University, which is equipped with PCs running under LINUX. The course is wheel chair accessible.  All disabilities will be accommodated. Handicapped individuals are encouraged to apply.  

Travel stipends of up to $1Knowledge genetic association analysis,000 each genetic epidemiology and/or statistical genetics are availablescreening criteria for the selection of participants.  Eligibility requirements are: (1) sufficient background and practical   Please describe your experience in statistical analysis detail in your application. It is helpful if you also enclose a copy of genetic data, and (2) demonstrated financial needyour CV. Preference for stipends will be given We may contact you personally to pre-doctoral students and postdoctoral researchersdiscuss your application. To apply for such a stipend, please attach a letter Although experience of request and enclose a letter using LINUX is not necessary it is highly beneficial to have basic knowledge of reference and proof this operating system before the start of student or postdoctoral statusthe course.

Knowledge genetic association analysisFor additional information, genetic epidemiology andplease contact [mailto:montagk@rockefeller.edu?subject=Rockefeller Advanced Gene Mapping Course 2021 Katherine Montague]: <br /or statistical genetics are screening criteria for selection of participants>email: [mailto:montagk@rockefeller.  Please describe your experience in detail in your application. It is helpful if you also enclose a copy of your CV. We may contact you personally to discuss your application. Although experience of using LINUX is not necessary it is highly beneficial to have basic knowledge of this operating system before the start of the courseedu montagk@rockefeller.edu] <br /><br /> 

For additional information, please contact on the scientific program contact the course organizer [mailto:montagksuzannemleal@rockefellergmail.educom?subject=Rockefeller Advanced Gene Mapping Course 2020 Katherine Montague2021 Suzanne Leal]: <br />email: [mailto:montagksuzannemleal@rockefellergmail.com suzannemleal@gmail.com] or [mailto:sml3@cumc.columbia.edu montagksml3@rockefellercumc.columbia.edu] <br />Tel: +1 (212) 327-7979 <br /> 

==Course Photo==[[File:142FBA93-B26F-45A4-A0C5-264B812AB558Applications are no longer being accepted.JPG|thumb|none|300px]]

* [http://www.statgen.us/files/20202021/01/docs02/lectures/NY2020NY2021-lecture1-nopause_4nopause.pdf Genome-wide association studies (GWAS) - Part 1]* [http://www.statgen.us/files/2020/012021/docs02/lectures/NY2020NY2021-lecture2-nopause_4nopause.pdf Genome-wide association studies (GWAS) - Part 2]

* [[Tutorials#FastLMM | http://statgen.us/files/2021/02/exercises/FASTLMM-NY2020.pdf Family-based Association using FaST-LMM, PLINK and R]] | * [httpshttp://githubstatgen.comus/statgeneticsfiles/statgen-courses2021/blob02/masterexercises/docker/fastlmmGCTA-gctaNY2021.dockerfile dockefile] and [https://hub.docker.com/r/statisticalgenetics/fastlmm-gcta/tags docker imagepdf GCTA]* [[Tutorials#GCTA|GCTA]] | [httpshttp://github.com/statgenetics/statgen-courses/blob/master/docker/fastlmm-gcta.dockerfile dockefile] and [https:us/files/hub.docker.com2021/r02/statisticalgeneticsexercises/fastlmmEpistasis-gcta/tags docker image]* [[Tutorials#Epistasis_NY2020.28PLINK_and_CASSI.29 | pdf Interaction analysis using PLINK and CASSI]] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/epistasis.dockerfile dockerfile] and [https://hub.docker.com/r/statisticalgenetics/epistasis/tags docker image]

* [http://www.statgen.us/files/2020/012021/docs02/lectures/LealCourse_Cox_Jan2020LealCourse_Cox_Jan2021.pdf Integrative Approaches in Biobanks: Getting to Biological Mechanisms of Disease]

[http://www.statgen.us/files/2021/02/bios/about_atd.pdf About Andy DeWan] ====LecturesLecture====* [http://www.statgen.us/files/20202021/02/lectures/DeWan_Adv_Gene_Mapping_Mendelian%20Randomization.pdf Mendelian randomization]* [http://statgen.us/files/012021/docs02/lectures/Rockefeller_Adv_Course_DeWan_pleiotropy_4Rockefeller_Adv_Course_DeWan_pleiotropy.pdf From cross-phenotype associations to pleiotropy in human genetic studiesPleiotropy]

* [[Tutorials#Pleiotropy|http://statgen.us/files/2021/02/exercises/pleio_exercise.pdf Pleiotropy]] | * [httpshttp://githubstatgen.comus/files/2021/02/exercises/pleio_exercise_answers.pdf Answers to Pleitropy Exercise]* [http:/statgenetics/statgen-courses.us/blobfiles/master2021/docker02/pleiotropyexercises/MR_exercise.dockerfile dockefilepdf Mendelian Randomization] and * [httpshttp://hubwww.dockerstatgen.comus/rfiles/statisticalgenetics2021/pleiotropy02/tags docker imageexercises/MR_exercise_answers.pdf Mendelian Randomization Answers]

* [http://www.statgen.us/files/2020/012021/docs02/lectures/data_quality_control_1.pdf Data Quality Control]* [http://www.statgen.us/files/20202021/01/docs02/lectures/NGS_data_qc.pdf NGS Data Quality Control]* [http://www.statgen.us/files/20202021/01/docs02/lectures/analysis_rare_variants_part_1.pdf Complex Trait Association Analysis of Rare VariantsObtained from Sequence Data: Population-Based Data]* [http://www.statgen.us/files/2020/012021/docs02/lectures/power_sample_sizes.pdf Power Analysis for Single and Rare Variant Aggregate Association Analyses]* [//www.statgen.us/files/2020/01/docs/lectures/Analysis_rare_variants_part_2.pdf National Heart Lung and Blood Institute Exome Sequencing Project]

* [[Tutorials#PSEQ|PLINK/SEQ (PSEQ)]] | [httpshttp://githubstatgen.comus/statgeneticsfiles/statgen-courses2021/blob02/masterexercises/docker/pseqPSEQ_exercise.dockerfile dockefilepdf PLINK/SEQ (PSEQ)] and * [httpshttp://hub.dockerstatgen.comus/rfiles/statisticalgenetics2021/pseq02/tags docker image]* [[Tutorials#Variant_Association_Tools|exercises/VAT_2021.pdf Association Analysis of Sequence Data using Variant Association Tools for Complex Traits]] | * [httpshttp://githubstatgen.comus/statgeneticsfiles/statgen-courses2021/blob02/masterexercises/docker/vatArmitage_sample_size.dockerfile dockerfilepdf Cochran Armitage Trend Test for GWAS power analysis] and * [httpshttp://hub.dockerstatgen.comus/rfiles/statisticalgenetics2021/vat02/tags docker imageexercises/FunctionalAnnotation.2021.pdf ANNOVAR Annotation]* [[Tutorials#Cochran_Armitage_Trend_Test|Cochran Armitage Trend Test http://statgen.us/files/2021/02/exercises/GWAS_Data_Controlling_for_Substructure_V2.pdf Genome-Wide Association - Association Analysis Controlling for GWAS power analysis]Population Substructure]* [[Tutorials#Annotation|ANNOVAR Annotation]] | [httpshttp://githubstatgen.comus/statgeneticsfiles/statgen-courses2021/blob02/masterexercises/docker/annovarPLINK_data_QC_V2.dockerfile dockefilepdf Genome-Wide Association Analysis - Data Quality Control] and  ===Judy Matuk===[httpshttp://hubwww.dockerstatgen.comus/rfiles/statisticalgenetics2021/annovar02/tags docker imagebios/about_jm.pdf About Judy Matuk]

* [http://statgen.us/files/2021/02/lectures/Rockefeller_draft_HSR%20Ethics%20and%20Regulations%20PPT_%20jm%201.18.2021.pdf Human Subject Training] ===Jurg Ott===[http://www.statgen.us/files/20202021/0102/docsbios/lectures/finemapping_pasaniucabout_jo.pdf Statistical fine-­mapping of GWAS signalsAbout Jurg Ott]<!--====ExercisesLectures====* finemap[http://www.statgen.us/files/2021/02/lectures/FPMforInteractions2021-01.pptx Frequent Pattern Mining Methods for Finding SNP->SNP Interactions]

* [http://www.statgen.us/files/2020/012021/docs02/lectures/Rockefeller_pop_gen_2020Rockefeller_complex_traits_2021.pdf Population GeneticsComplex Traits]* [http://www.statgen.us/files/20202021/01/docs02/lectures/Rockefeller_complex_traits_2020Rockefeller_functional_annotation_2021.pdf Evolution, maintenance and allelic architecture of complex traitsFunctional Annotation]* [http://www.statgen.us/files/20202021/01/docs02/lectures/Rockefeller_polygenic_2020Rockefeller_polygenic_risk_score_2021.pdf Polygenic Risk Score]* [http://statgen.us/files/2021/02/lectures/Rockefeller_population_genetics_2021.pdf Population Genetics] ===Gao Wang===[http://www.statgen.us/files/20202021/0102/docsbios/about_gw.pdf About Gao Wang] ====Lectures====* [http://statgen.us/files/2021/02/lectures/Rockefeller_function_2019Lecture_Univariate_Fine_Mapping.pdf Functional AnnotationStatistical fine-mapping]* [http://statgen.us/files/2021/02/lectures/Lecture_Multivariate_Analysis.pdf Multivariate analysis]

* [[Tutorials#Polygenic_risk_prediction_https://github.28NPS_methodcom/statgenetics/statgen-courses/raw/master/handout/finemapping.29|Polygenic risk prediction using nondocx Statistical fine-parametric shrinkage]mapping in association studies] | [https://github.com/statgenetics/statgen-courses/blob/master/docker/npsfinemap.dockerfile dockefiledockerfile] and [https://hub.docker.com/r/statisticalgenetics/npsfinemap/tags docker image]* [https://github.com/statgenetics/statgen-courses/raw/master/handout/finemapping_answers.docx Answers to fine-mapping exercise questions]