Changes

The course emphasis is on the analysis of complex human disease traits; concentrating on methods to detect rare and common variant associations. The course includes theory as well as practical exercises. The exercises will be carried out using a variety of computer programs including BEAM3, GERP, GotCloud, GenAbel, Matrix-eQTL, PLINK, PrediXCan, Polyphen-2, R, SEQPower, Variant Association Tools (VAT), etc. Topics include: Analysis of whole genome association studies; analysis of rare variants using next-generation sequence data; analysis of qualitative and quantitative traits (population and family-based data); Linear mixed models; eQTL mapping; prediction models using RNAseq and array data; inferences for heritability estimation and prediction; functional prediction of variant sites, variant annotation; variant calling, controlling for population substructure\admixture (principal components analysis\multidimensionality scaling); data quality control of genotype and sequence data; meta-analysis; gene x gene interaction; sample size estimation and evaluating power for common and rare variants.

The maximum number of participants is 30. The course will take place in the Great Hall in Welch at The Rockefeller University, which is equipped with PCs running under LINUXStudents will perform exercises by connecting to the cloud using their own laptops. Laptops are also available for students to use for the duration of the course. The course is wheelchair accessible. All disabilities will be accommodated. Handicapped individuals are encouraged to apply.

Knowledge genetic association analysis, genetic epidemiology and/or statistical genetics are screening criteria for selection of participants. Please describe your experience in detail in your application. We may contact you personally to discuss your application. Although the experience of using LINUX is not necessary it is highly beneficial to have basic knowledge of this operating system before the start of the course.

[httpshttp://statgen.research.bcm.eduus/files/2018/01/info2019/Application_Advanced_Gene_Mapping_Jan_2018Rockefeller_advanced_course_flyer_2019.htm pdf Click here for application formcourse flyer]– Please Post and Distribute

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===Lecture Handouts=======Gon&ccedil;alo Abecasis====* Presentations** [httpshttp://statgen.researchus/files/2019/01/slides/abecasis/00.bcm%20Warm-up%20to%20Genomewide%20Analyses.edupdf Genome-wide Analysis]** [http://statgen.us/files/2019/01/slides/abecasis/01.%20Genotype%20Imputation.pdf Genotype Imputation]** [http://statgen.us/files/2019/01/slides/abecasis/02.%20Meta-Analysis.pdf Meta Analysis]** [http://statgen.us/files/2019/01/slides/abecasis/03.%20Sequencing.pdf Sequencing]<!--* Data Sets** [http://statgen.us/files/2018/01/infoabecasis/adv_gene_mapping_schedule_2018exercises.tar.gz Download]--> ====Heather Cordell====* Presentations** [http://statgen.us/files/2019/01/slides/cordell/hjc-NY2016-GWAS-nopage.pdf Click here Genome-wide Association Studies - case/control and family-based]** [http://statgen.us/files/2019/01/slides/cordell/hjc-NY2019-MixedModels-nopage.pdf Mixed Models and Family-Based Methods]* Exercises** [http://statgen.us/files/2019/01/slides/cordell/Computer%20Practical%20Exercise.pdf Family-based Association Analysis - FaST-LMM, PLINK and R]** [http://statgen.us/files/2019/01/slides/cordell/Computer%20Practical%20Exercise%202.pdf Mixed models Association Analysis Computer - GCTA, PLINK, and R] ====Nancy Cox====* Presentations** [http://statgen.us/files/2019/01/slides/cox/DataIntegration_Cox_Lecture2_NJC_2019.pdf Data Integration] ====Suzanne Leal====* Presentations** [http://statgen.us/files/2019/01/slides/leal/data_quality_control_1.pdf Data Quality Control]** [http://statgen.us/files/2019/01/slides/leal/NGS_data_qc.pdf NGS Data Quality Control]** [http://statgen.us/files/2019/01/slides/leal/analysis_rare_variants.pdf Complex Trait Association Analysis of Rare Variants]** [http://statgen.us/files/2019/01/slides/leal/Trio_and_Family_Based_Association_analysis_3_new_format.pdf Family Based Rare Variant Association Analysis: Trios, Sibpairs and Extended Families]** [http://statgen.us/files/2019/01/slides/leal/power_sample_sizes.pdf Power Analysis for course scheduleIndividual Variants and Rare Variant Aggregate Association Analysis] ====Shamil Sunyaev====* Presentations** [http://statgen.us/files/2019/01/slides/sunyaev/Rockefeller_polygenic_2019.pdf Genetic Risk Prediction]** [http://statgen.us/files/2019/01/slides/sunyaev/Rockefeller_complex_traits_2019.pdf Evolution, maintenance and allelic architecture of complex traits]** [http://statgen.us/files/2019/01/slides/sunyaev/Rockefeller_function_2019.pdf Annotating gene sequence variation]** [http://statgen.us/files/2019/01/slides/sunyaev/Rockefeller_pop_gen_2019.pdf Intro to population genetics] ===Practical Exercises===* [http://statgen.us/files/2019/01/exercise_booklet_1_24_19.pdf Exercise Booklet] * [http://statgen.us/files/tutorials/gwas-qc/PLINK_data_QC_V2.pdf Genome-wide Association Analysis - Quality Control - PLINK]* [http://statgen.us/files/tutorials/gwas-substructure/GWAS_Data_Controlling_for_Substructure_V2.pdf Genome-wide Association Analysis - MDS and PCA – PLINK]* [http://statgen.us/files/tutorials/vat/VAT_exercise_2019_1_nographs.pdf Sequence data quality control and association analysis (VAT)]* [http://statgen.us/files/tutorials/pseq/PSEQ_exercise_2019.pdf Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)]* [http://statgen.us/files/tutorials/rvtdt/rvtdt_exercise_v3.pdf Rare-Variant Transmission Disequilibrium Test (RV-TDT)]* [http://statgen.us/files/tutorials/Armitage_sample_size_revised.pdf Power and Sample Size Calculations – Cochran Armitage Test for Trend ]* [http://statgen.us/files/tutorials/functional-annotation/FunctionalAnnotation_exercise_2019.pdf Functional Annotation] * [http://csg.sph.umich.edu/abecasis/MaCH/tour/ MaCH]* [https://genome.sph.umich.edu/wiki/METAL_Quick_Start METAL]* [https://genome.sph.umich.edu/wiki/Tutorial:_RAREMETAL RAREMETAL] ===Exercise Data Sets===* [http://statgen.us/files/2019/01/datasets/Plink_DataQC.tar.gz Genome-wide Association Analysis - Quality Control - PLINK]* [http://statgen.us/files/2019/01/datasets/Plink_substructure.tar.gz Genome-wide Association Analysis - MDS and PCA – PLINK]* [http://statgen.us/files/2019/01/datasets/FASTLMMLGCTA.tar.gz Family-based Association Analysis- FaST-LMM, PLINK]* [http://statgen.us/files/2019/01/datasets/FASTLMMLGCTA.tar.gz Mixed models Association Analysis Computer – GCTA, PLINK and R]* [http://statgen.us/files/2019/01/datasets/Plink_DataQC.tar.gz Sequence data quality control and association analysis (VAT)]* [http://statgen.us/files/2019/01/datasets/pseq.tar.gz Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)]* [http://statgen.us/files/2019/01/datasets/rvtdt.tar.gz Rare-Variant Transmission Disequilibrium Test (RV-TDT)]* [http://statgen.us/files/2019/01/datasets/FunctionalAnnotation.tar.gz Functional Annotation]* [http://statgen.us/files/2019/01/datasets/mach.tar.gz MaCH]* [http://statgen.us/files/2019/01/datasets/metal.tar.gz METAL]* [http://statgen.us/files/2019/01/datasets/raremetal.tar.gz RAREMETAL] ===Commands===* [[Genome-wide Association-Quality Control Exercise|Genome-wide Association Analysis-Quality Control-PLINK]]* [[Genome-wide Association-MDS and PCA Exercise|Genome-wide Association Analysis-MDS and PCA-PLINK]]* [[Family-based Association Exercise|Family-based Association Analysis- FaST-LMM, PLINK and R]]* [[Mixed models Association Analysis_Exercise|Mixed models Association Analysis Computer – GCTA, PLINK and R]]* [[VAT_Exercise|Sequence data quality control and association analysis (VAT)]]* [[PSEQ_Exercise|Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)]]* [[RV-TDT_Exercise|Rare-Variant Transmission Disequilibrium Test (RV-TDT)]]* [[Functional Annotation_Exercise|Functional Annotation]] ===Software===* [http://www.openbioinformatics.org/annovar/ ANNOVAR]* [https://github.com/MicrosoftGenomics/FaST-LMM FasT-LLM]* [https://cnsgenomics.com/software/gcta/ GCTA]* [https://genome.sph.umich.edu/wiki/MaCH MaCH]* [https://genome.sph.umich.edu/wiki/METAL METAL]* [https://genome.sph.umich.edu/wiki/Minimac Minimac]* [http://zzz.bwh.harvard.edu/plink/ PLINK]* [https://atgu.mgh.harvard.edu/plinkseq/ PLINK/SEQ]* [https://genome.sph.umich.edu/wiki/RAREMETAL RAREMETAL]* [[RV-TDT|RV-TDT]]* [http://bioinformatics.org/spower/ SEQPower]* [http://varianttools.sourceforge.net/ Variant Association Tools]