Last updated: 2022-07-27

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Knit directory: SISG2022_Association_Mapping/

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Instructors: Joelle Mbatchou & Loic Yengo

You will find on this website link to lecture slides, exercises including some solutions, and link to the class video recordings.

The official SISG web page can be found here (requires login) – course evaluations and certificates of completion are available via this page.

Session Format

The module has 10 sessions, each of 90 minutes. The standard format for a session is approximately:

  • 45 minutes of lecture material that will be recorded via Zoom live and posted at the end of the day
  • 30 minutes of exercises for you to try, with small-group “breakout” Zoom sessions available, attended by other class participants, and Teaching Assistants
  • 15 minute discussion of exercises, where the instructors will present possible solutions and answer questions

Please join the module’s Slack channel, where you can ask questions and see real-time updates from the instructors and TAs. Each session builds on previous sessions so you will get maximum benefit by attending every session live and in sequence.

The course schedule is below.

Pre-requisites

We will use an online server during the module to run exercises (see instructions here for setup). If you decide to run analyses from your local machine instead, follow the instructions below.

Prior to the module, please install working and latest versions of:

All are free software.

Please be sure to install some necessary R packages with:

install.packages("qqman")
install.packages("bigsnpr")
install.packages("hexbin")
install.packages("tidyverse")
install.packages("BEDMatrix")
install.packages("devtools")
install.packages("SKAT")
install.packages("patchwork")
devtools::install_github("yaowuliu/ACAT")
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("GWASTools")

Schedule

All times listed below for the schedule are Pacific Daylight Time (PDT, Seattle time).

Monday, July 25th
Time Session Topic Lecture Exercises Key
8:00am-9:30am 1 Introduction, Case Control Association Testing & Association Testing with Quantitative Traits Intro, Lecture Exercises HTML, Rmd
10am-11:30am 2 Introduction to the PLINK Software for GWAS & Population Structure Inference Lecture Exercises HTML, Rmd
12pm-1:30pm 3 GWAS in Samples with Structure & Introduction to the REGENIE Software Lecture Exercises HTML, Rmd
1:45pm-2:30pm 4 Power, Sample Size & Design Considerations Lecture Exercises HTML, Rmd

Link to Day 1 video: Zoom recording

Tuesday, July 26th
Time Session Topic Lecture Exercises Key
8:00am-9:30am 5 Downstream analyses: Conditional Analyses, Colocalization, Fine-mapping, Gene-based & Pathways Analysis Lecture Exercises HTML, Rmd
10am-11:30am 6 Downstream analyses: Polygenic Risk Scores Lecture Exercises HTML, Rmd
12pm-1:30pm 7 Rare Variant Analysis: Collapsing Tests, Kernel (Variance Component) Tests and Omnibus Tests Lecture Exercises HTML, Rmd
1:45pm-2:30pm 8 Emerging issues showcasing ongoing research Lecture Exercises HTML, Rmd

Link to Day 2 video: Zoom recording

Wednesday, July 27th
Time Session Topic Lecture Exercises Key
8:00am-9:30am 9 Beyond traditional GWAS: Variance QTL, Interaction Testing, GWAX, Time-to-event, Multi-trait analysis Lecture Exercises HTML, Rmd
10am-11am 10 Emerging issues showcasing ongoing research Lecture

Link to Day 3 video: Zoom recording

Datasets

All the data sets used can be downloaded from the Github repository. These have all been loaded on the online server for the class.

Additional resources


sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
 [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
 [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
[10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dplyr_1.0.9     workflowr_1.7.0

loaded via a namespace (and not attached):
 [1] tidyselect_1.1.2  xfun_0.31         bslib_0.3.1       purrr_0.3.4      
 [5] colorspace_2.0-3  vctrs_0.4.1       generics_0.1.3    viridisLite_0.4.0
 [9] htmltools_0.5.2   yaml_2.3.5        utf8_1.2.2        rlang_1.0.3      
[13] later_1.3.0       pillar_1.7.0      jquerylib_0.1.4   glue_1.6.2       
[17] DBI_1.1.3         lifecycle_1.0.1   stringr_1.4.0     munsell_0.5.0    
[21] rvest_1.0.2       kableExtra_1.3.4  evaluate_0.15     knitr_1.39       
[25] callr_3.7.0       fastmap_1.1.0     httpuv_1.6.5      ps_1.7.1         
[29] fansi_1.0.3       Rcpp_1.0.9        promises_1.2.0.1  scales_1.2.0     
[33] webshot_0.5.3     jsonlite_1.8.0    systemfonts_1.0.4 fs_1.5.2         
[37] digest_0.6.29     stringi_1.7.6     processx_3.7.0    getPass_0.2-2    
[41] rprojroot_2.0.3   cli_3.3.0         tools_4.2.1       magrittr_2.0.3   
[45] sass_0.4.1        tibble_3.1.7      crayon_1.5.1      whisker_0.4      
[49] pkgconfig_2.0.3   ellipsis_0.3.2    xml2_1.3.3        svglite_2.1.0    
[53] assertthat_0.2.1  rmarkdown_2.14    httr_1.4.3        rstudioapi_0.13  
[57] R6_2.5.1          git2r_0.30.1      compiler_4.2.1