Changes

From Statistical Genetics Courses

Jump to: navigation, search

Tutorials

1,143 bytes added, 16:45, 9 November 2021
/* Fine-mapping (SuSiE method) */
Starting Fall 2019 we adopt [https://www.docker.com/ docker] to run our course material . We have created various [https://hub.docker.com/u/statisticalgenetics docker repositories] with source material freely available from [https://github.com/statgenetics/statgen-courses github] for users to readily setup and reproduce our tutorials on their own computers. These docker images can also be used as production tool to run relevant software on your computer (Mac, Linux or Windows) or even a high performance computing cluster (if properly configured) for your own data analysis.
 ===General instructions===
* [https://github.com/statgenetics/statgen-courses/wiki/How-to-launch-course-tutorials#alternative-to-cloud-server-use-your-own-computer Instructions to setup course tutorial environment on your computer]
* [https://github.com/statgenetics/statgen-courses/wiki/How-to-launch-course-tutorials#option-1-launch-exercise-in-jupyterlab Instructions to run course tutorial through JupyterLab]
===Tutorial specific instructions===
 
We use a script [https://github.com/statgenetics/statgen-courses/blob/master/src/statgen-setup "statgen-setup"] to start the docker based environments for these tutorials. Please refer to the previous section for instructions on the installation of this script.
 
Material and instructions for specific exercise are listed in each section below (''only those using statgen-setup command are relevant to our docker based tutorials''). They provide links to materials and a minimal set of commands to use for launching and running an exercise.
* [http://gmc.mdc-berlin.de/alohomora/ Software Link]
==AnnotationAnnovar complex traits==
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/FunctionalAnnotation.pdf Functional Annotation Exercise <nowiki>[PDF]</nowiki>]
* [[Commands in Annotation Exercise|Exercise Commands]]
</pre>
==Annovar MEndelianMendelian traits==
* [http://statgen.us/files/tutorials/FunctionalAnnotation_Annovar_final.pdf Exercise <nowiki>[PDF]</nowiki>]
* [https://statgen.us/files/2017/09/commands/annovar-functional_annotation.txt Commands Part I - Functional Annotation]
==Cochran Armitage Trend Test==
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/Armitage_sample_size.pdf CATT Exercise <nowiki>[PDF]</nowiki>]
 
</pre>
 
==Fine-mapping (SuSiE method)==
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/finemapping.docx susieR Exercise <nowiki>[DOCX]</nowiki>]
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/finemapping_answers.docx susieR Exercise Answers <nowiki>[DOCX]</nowiki>]
* [https://github.com/statgenetics/statgen-courses/blob/master/notebooks/finemapping.ipynb susieR Exercise <nowiki>[Ipython notebook]</nowiki>]
* [https://github.com/statgenetics/statgen-courses/blob/master/notebooks/finemapping_answers.ipynb susieR Exercise Answers <nowiki>[Ipython notebook]</nowiki>]
 
 
To run the exercise from docker image provided,
 
<pre>statgen-setup launch --tutorial finemap
</pre>
==GCTA==
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/IGV.docx IGV exercise <nowiki>[DOCX]</nowiki>]
* [http://statgen.us/files/igv_exercise.zip Exercise files (VCF and BAM)]
 
==PSEQ==
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/PSEQ.pdf PSEQ Exercise <nowiki>[PDF]</nowiki>]
* [[https://github.com/statgenetics/statgen-courses/blob/master/notebooks/PSEQ.ipynb PSEQ Commands in Exercise|Exercise Commands<nowiki>[Ipython Notebook]</nowiki>]
To run the exercise from docker image provided,
<pre>statgen-setup login launch --tutorial pseq
</pre>
Notice that since PSEQ exercise does not involve generating and visualizing plots, it is also fine to use a command terminal, instead of the JupyterLab server, to run this exercise and reproduce exactly what was described in the tutorial. To do so,
 
<pre>statgen-setup login --tutorial pseq
</pre>
==REGENIE==
to load the data-set to the JupyterLab workspace.