Latest revision as of 18:06, 18 April 2017

Complex Trait Analysis of Next Generation Sequence Data

March 6-10, 2017, Max Delbrück Center (MDC) for Molecular Medicine, Berlin, Germany

Course Participants

General Information

The goal of the course is to teach the course participants both the theory and application of methods to analyze next generation sequence (NGS) data for human complex traits. Attendees will learn how to design studies, call variants from NGS data, analysis of population-, trio- and family-based sequence data and evaluation of variant functionality. Analyses will include performing complex trait rare variant association analysis for population and trio data. Exercises will be carried out using a variety of computer programs (GATK, IGV, Polyphen2, PSEQ, SEQPower, and Variant Association Tools (VAT)). TOPICS will be include: sequence alignment, calling variants from NGS data, quality control of NGS data, association testing framework for quantitative and qualitative traits (fixed effects, random effects and mixed models), rare variant association methods, estimating power and sample size for rare variant association studies, imputation of rare variants and their analysis, detecting putative causal variants for complex traits and evaluating variant functionality.

Link to Berlin hotel tax exemption form

Direction to the MDC Campus

Direction to the classroom

Location:

MDC - communication center (Building C83 on the Campus Map)

Room Axion 2

The building is red and stands across the street from the campus bus stop and the blue bear. The instructors for the course are Suzanne Leal (Baylor College of Medicine) and Michael Nothnagel (University of Cologne). The cost of the 5 day course is 975 EUR for researchers from an academic institution, and 1,950 EUR for individuals from private (for profit) companies. This fee covers tuition, Monday evening wine and cheese party and course related expenses (handouts, etc.) but not room, board or meals. Inexpensive housing is available for course participants at the MDC and nearby hotels. The maximum number of participants is 40. The cost of the 5 day course is 975 EUR for researchers from an academic institution, and 1,950 EUR for individuals from private (for profit) companies. This fee covers tuition, Monday evening wine and cheese party and course related expenses (handouts, etc.) but not room, board or meals. Inexpensive housing is available for course participants at the MDC and nearby hotels. The maximum number of participants is 40. For additional information on the course please contact Suzanne Leal:

email: sleal@bcm.edu
Tel: +1 (713) 798-4011
Fax: +1 (713) 798-4012

Instructors

The instructors for the course are Suzanne Leal (Baylor College of Medicine) and Michael Nothnagel (University of Cologne).

Course Slides

Data-sets Used During the Course

Commands

Result Files

GATK/IGV exercise

Software Links

Bioinformatic Tools

Click here for course schedule

Click here for the application form

Click here for course flyer (please post and distribute)

@@ Line 2: / Line 2: @@
 =Complex Trait Analysis of Next Generation Sequence Data=
-===March 6-10, 2017<br data-attributes="%20/">Max Delbrück Center (MDC) for Molecular Medicine<br data-attributes="%20/">Berlin, Germany===
+March 6-10, 2017, Max Delbrück Center (MDC) for Molecular Medicine, Berlin, Germany
-The third annual course on Complex Trait Analysis of Next Generation Sequence Data will be held at the MDC in Berlin from March 6-10, 2017. The goal of the course is to teach the course participants both the theory and application of methods to analyze next generation sequence (NGS) data for human complex traits. Attendees will learn how to design studies, call variants from NGS data, analysis of population-, trio- and family-based sequence data and evaluation of variant functionality. Analyses will include performing complex trait rare variant association analysis for population and trio data. Exercises will be carried out using a variety of computer programs (GATK, IGV, Polyphen2, PSEQ, SEQPower, and Variant Association Tools (VAT)). TOPICS will be include: sequence alignment, calling variants from NGS data, quality control of NGS data, association testing framework for quantitative and qualitative traits (fixed effects, random effects and mixed models), rare variant association methods, estimating power and sample size for rare variant association studies, imputation of rare variants and their analysis, detecting putative causal variants for complex traits and evaluating variant functionality.
+===Course Participants===
+[[File:2017-03-Participants.jpg|none|500x375px]]
+===General Information===
+<!--The third annual course on Complex Trait Analysis of Next Generation Sequence Data will be held at the MDC in Berlin from March 6-10, 2017.-->The goal of the course is to teach the course participants both the theory and application of methods to analyze next generation sequence (NGS) data for human complex traits. Attendees will learn how to design studies, call variants from NGS data, analysis of population-, trio- and family-based sequence data and evaluation of variant functionality. Analyses will include performing complex trait rare variant association analysis for population and trio data. Exercises will be carried out using a variety of computer programs (GATK, IGV, Polyphen2, PSEQ, SEQPower, and Variant Association Tools (VAT)). TOPICS will be include: sequence alignment, calling variants from NGS data, quality control of NGS data, association testing framework for quantitative and qualitative traits (fixed effects, random effects and mixed models), rare variant association methods, estimating power and sample size for rare variant association studies, imputation of rare variants and their analysis, detecting putative causal variants for complex traits and evaluating variant functionality.
 =====[http://statgen.us/files/2015/09/BerlinHotelTaxExemptionForm.pdf Link to Berlin hotel tax exemption form]=====
 =====[https://www.mdc-berlin.de/directions Direction to the MDC Campus]=====
@@ Line 17: / Line 21: @@
 The cost of the 5 day course is 975 EUR for researchers from an academic institution, and 1,950 EUR for individuals from private (for profit) companies. This fee covers tuition, Monday evening wine and cheese party and course related expenses (handouts, etc.) but not room, board or meals. Inexpensive housing is available for course participants at the MDC and nearby hotels. The maximum number of participants is 40.
 The cost of the 5 day course is 975 EUR for researchers from an academic institution, and 1,950 EUR for individuals from private (for profit) companies. This fee covers tuition, Monday evening wine and cheese party and course related expenses (handouts, etc.) but not room, board or meals. Inexpensive housing is available for course participants at the MDC and nearby hotels. The maximum number of participants is 40.
 For additional information on the course please contact [mailto:sleal@bcm.edu?subject=Genetic%20Association%20Course%2C%20Berlin%202015 Suzanne Leal]:
 <!--Application Deadline January 5, 2017-->
-* email: [mailto:sleal@bcm.edu;suzannemleal@gmail.com?subject=Genetic%20Association%20Course%20Berlin%202016 sleal@bcm.edu]
+:
-* Tel: +1 (713) 798-4011
+:* email: [mailto:sleal@bcm.edu;suzannemleal@gmail.com?subject=Genetic%20Association%20Course%20Berlin%202016 sleal@bcm.edu]
-* Fax: +1 (713) 798-4012
+:* Tel: +1 (713) 798-4011
+:* Fax: +1 (713) 798-4012
 ===Instructors===
 The instructors for the course are [https://www.bcm.edu/research/labs/center-for-statistical-genetics/ Suzanne Leal] (Baylor College of Medicine) and [http://portal.ccg.uni-koeln.de/ccg/research/stat-gen-bioinformatics/ Michael Nothnagel] (University of Cologne).
-[[250px]]
+[[File:2017-03-Instructors.jpg|none|250x333px]]
-<!--[[File:2017-03-Instructors.jpg|center|frame]]-->
 ===[http://statgen.us/files/2017/03/auth/coursebook_lectures.pdf Course Slides]===
 ===Data-sets Used During the Course===
-::* [http://statgen.us/files/2016/07/annotation.tar.bz2 Annotation exercise]
+:::* [http://statgen.us/files/2016/07/annotation.tar.bz2 Annotation exercise]
-::* [http://statgen.us/files/2016/07/gatk.tar.bz2 GATK/IGV exercise]
+:::* [http://statgen.us/files/2016/07/gatk.tar.bz2 GATK/IGV exercise]
-::* [http://statgen.us/files/2016/07/pseq.tar.bz2 PSEQ exercise]
+:::* [http://statgen.us/files/2016/07/pseq.tar.bz2 PSEQ exercise]
-::* [http://statgen.us/files/2016/07/popgen.tar.bz2 PopGen exercise]
+:::* [http://statgen.us/files/2016/07/popgen.tar.bz2 PopGen exercise]
-::* [http://statgen.us/files/2016/07/regression.tar.bz2 Regression exercise]
+:::* [http://statgen.us/files/2016/07/regression.tar.bz2 Regression exercise]
-::* [https://statgen.research.bcm.edu/files/2016/09/exercises/rvtdt.tar.gz RV-TDT exercise]
+:::* [https://statgen.research.bcm.edu/files/2016/09/exercises/rvtdt.tar.gz RV-TDT exercise]
-::* [http://statgen.us/files/2016/07/seqpower.tar.bz2 SEQPower exercise]
+:::* [http://statgen.us/files/2016/07/seqpower.tar.bz2 SEQPower exercise]
-::* [http://statgen.us/files/2016/07/vat.tar.bz2 Variant Association Tools exercise]
+:::* [http://statgen.us/files/2016/07/vat.tar.bz2 Variant Association Tools exercise]
+:
 ===Commands===
-::* [[Annotation_Exercise|Annotation]]
+:::* [[Annotation_Exercise|Annotation]]
-::* [[GATK_IGV_Exercise|GATK/IGV]]
+:::* [[GATK_IGV_Exercise|GATK/IGV]]
-::*[[Popgen_Exercise|Popgen]]
+:::* [[Popgen_Exercise|Popgen]]
-::* [[PSEQ_Exercise|PSEQ]]
+:::* [[PSEQ_Exercise|PSEQ]]
-::* [[Regression_Exercise|Regression]]
+:::* [[Regression_Exercise|Regression]]
-::* [[RV-TDT_Exercise|RV-TDT]]
+:::* [[RV-TDT_Exercise|RV-TDT]]
-::* [[SEQPower_Exercise|SEQPower]]
+:::* [[SEQPower_Exercise|SEQPower]]
-::* [[VAT_Exercise|VAT]]
+:::* [[VAT_Exercise|VAT]]
+:
 ===Result Files===
-::* [http://statgen.us/files/2016/07/gatk_results.tar.gz GATK/IGV exercise]
+:::* [http://statgen.us/files/2016/07/gatk_results.tar.gz GATK/IGV exercise]
+:
 ===Software Links===
-::* [https://www.broadinstitute.org/gatk/ GATK]
+:::* [https://www.broadinstitute.org/gatk/ GATK]
-::* [http://www.broadinstitute.org/igv/ IGV] ([http://statgen.us/files/software/igv.jar Download JAR file])
+:::* [http://www.broadinstitute.org/igv/ IGV] ([http://statgen.us/files/software/igv.jar Download JAR file])
-::* [https://atgu.mgh.harvard.edu/plinkseq/ PSEQ]
+:::* [https://atgu.mgh.harvard.edu/plinkseq/ PSEQ]
-::* [https://www.r-project.org/ R]
+:::* [https://www.r-project.org/ R]
-::* [http://bioinformatics.org/rv-tdt/ RV-TDT]
+:::* [http://bioinformatics.org/rv-tdt/ RV-TDT]
-::* [http://www.bioinformatics.org/spower/start SEQPower]
+:::* [http://www.bioinformatics.org/spower/start SEQPower]
-::* [http://varianttools.sf.net/VAT Variant Association Tools]
+:::* [http://varianttools.sf.net/VAT Variant Association Tools]
+:
 ===Bioinformatic Tools===
-::* [http://cadd.gs.washington.edu/score CADD]
+:::* [http://cadd.gs.washington.edu/score CADD]
-::* [http://fathmm.biocompute.org.uk/inherited.html FATHMM]
+:::* [http://fathmm.biocompute.org.uk/inherited.html FATHMM]
-::* [http://mendel.stanford.edu/SidowLab/downloads/gerp/ GERP]
+:::* [http://mendel.stanford.edu/SidowLab/downloads/gerp/ GERP]
-::* [http://www.genetics.wustl.edu/jflab/lrt_query.html LRT]
+:::* [http://www.genetics.wustl.edu/jflab/lrt_query.html LRT]
-::* [http://www.mutationtaster.org/ChrPos.html Mutation Taster]
+:::* [http://www.mutationtaster.org/ChrPos.html Mutation Taster]
-::* [http://genome.ucsc.edu/cgi-bin/hgGateway Nucleotide Conservation]
+:::* [http://genome.ucsc.edu/cgi-bin/hgGateway Nucleotide Conservation]
-::* [http://compgen.bscb.cornell.edu/phast/ PhyloP]
+:::* [http://compgen.bscb.cornell.edu/phast/ PhyloP]
-::* [http://genetics.bwh.harvard.edu/pph2/bgi.shtml PolyPhen-2]
+:::* [http://genetics.bwh.harvard.edu/pph2/bgi.shtml PolyPhen-2]
-::* [http://provean.jcvi.org/genome_submit_2.php?species=human PROVEAN and SIFT]
+:::* [http://provean.jcvi.org/genome_submit_2.php?species=human PROVEAN and SIFT]
-::* [http://grch37.ensembl.org/Homo_sapiens/Tools/VEP VEP]
+:::* [http://grch37.ensembl.org/Homo_sapiens/Tools/VEP VEP]
+:
 [https://statgen.research.bcm.edu/files/2017/03/schedule_berlin_complex_ngs_2017.pdf Click here for course schedule]

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Difference between revisions of "ComplexNGS2017"

From Statistical Genetics Courses