Difference between revisions of "Tutorials"

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===General instructions===
 
===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#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]
 
* [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]
 
* [https://github.com/statgenetics/statgen-courses/wiki/How-to-launch-course-tutorials#option-2-launch-from-command-shell Instructions to run course tutorial through command line terminal]
 
* [https://github.com/statgenetics/statgen-courses/wiki/How-to-launch-course-tutorials#option-2-launch-from-command-shell Instructions to run course tutorial through command line terminal]
  
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===Preparing Your Computer===
 +
{| class="wikitable"
 +
|-
 +
||{{#ev:youtube|3K-sGzxsyK0|240|center|Linux}}
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||{{#ev:youtube|DRCDNBlxZ-w|240|center|Mac}}
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||{{#ev:youtube|sxv45NCSFMk|240|center|Windows}}
 +
|}
 +
 +
===Running Exercises===
 +
{{#ev:youtube|OgHvRVtIIog|320}}
  
 
===Tutorial specific instructions===
 
===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.
 
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.
+
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. Command "statgen-setup login" will allow you to start and login to a Linux command line environment (regardless of your current computational environment) to perform all analysis in command shells. This works for all the tutorials on this page. Additionally, some tutorials support command "statgen-setup launch" which will start a JupyterLab server to perform the analysis.
  
 
==Alohomora==
 
==Alohomora==
−
* [http://statgen.us/files/tutorials/seqspark/Alohomora_Exercise_revised.pdf Exercise <nowiki>[PDF]</nowiki>]
+
* [http://statgen.us/files/tutorials/Alohomora_Exercise_revised.pdf Exercise <nowiki>[PDF]</nowiki>]
 
* [https://statgen.research.bcm.edu/files/2016/10/data/alohomora.zip Data Set]
 
* [https://statgen.research.bcm.edu/files/2016/10/data/alohomora.zip Data Set]
 
* [http://gmc.mdc-berlin.de/alohomora/ Software Link]
 
* [http://gmc.mdc-berlin.de/alohomora/ Software Link]
  
−
==Annotation==
+
==Annovar complex traits==
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/FunctionalAnnotation.pdf Functional Annotation Exercise <nowiki>[PDF]</nowiki>]
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/FunctionalAnnotation.pdf Functional Annotation Exercise <nowiki>[PDF]</nowiki>]
 
* [[Commands in Annotation Exercise|Exercise Commands]]
 
* [[Commands in Annotation Exercise|Exercise Commands]]
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</pre>
 
</pre>
  
−
==Annovar MEndelian==
+
==Annovar Mendelian traits==
 
* [http://statgen.us/files/tutorials/FunctionalAnnotation_Annovar_final.pdf Exercise <nowiki>[PDF]</nowiki>]
 
* [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]
 
* [https://statgen.us/files/2017/09/commands/annovar-functional_annotation.txt Commands Part I - Functional Annotation]
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==Cochran Armitage Trend Test==
 
==Cochran Armitage Trend Test==
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/Armitage_sample_size.pdf CATT Exercise <nowiki>[PDF]</nowiki>]
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/Armitage_sample_size.pdf CATT Exercise <nowiki>[PDF]</nowiki>]
 +
  
  
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</pre>
 
</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==
 
==GCTA==
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==GWAS: Data Quality Control==
 
==GWAS: Data Quality Control==
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/PLINK_data_QC.pdf Exercise <nowiki>[PDF]</nowiki>]
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/PLINK_data_QC.pdf Exercise <nowiki>[PDF]</nowiki>]
 +
* [https://github.com/statgenetics/statgen-courses/blob/master/notebooks/PLINK_Data_QC.ipynb Exercise <nowiki>[IPython Notebook]</nowiki>]
 
* [[GWAS Data QC Exercise|Exercise Commands]]
 
* [[GWAS Data QC Exercise|Exercise Commands]]
  
−
To run the exercise from docker image provided,
+
To run the exercise via JupyterLab from docker image provided,
  
−
<pre>statgen-setup login --tutorial plink
+
<pre>statgen-setup launch --tutorial plink
 
</pre>
 
</pre>
  
 +
Alternatively, you can opt to run the exercise via command terminal from docker image provided,
 +
 +
<pre>statgen-setup login --tutorial plink
 +
</pre>
  
 
==GWAS: Association Analysis Controlling for Population Substructure==
 
==GWAS: Association Analysis Controlling for Population Substructure==
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/PLINK_Substructure.pdf Exercise <nowiki>[PDF]</nowiki>]
 
* [https://github.com/statgenetics/statgen-courses/blob/master/handout/PLINK_Substructure.pdf Exercise <nowiki>[PDF]</nowiki>]
 +
* [https://github.com/statgenetics/statgen-courses/blob/master/notebooks/PLINK_Substructure.ipynb Exercise <nowiki>[IPython Notebook]</nowiki>]
 
* [[GWAS_Controlling_for_Population_Substructure|Exercise Commands]]
 
* [[GWAS_Controlling_for_Population_Substructure|Exercise Commands]]
  
−
To run the exercise from docker image provided,
+
To run the exercise via JupyterLab from docker image provided,
  
−
<pre>statgen-setup login --tutorial plink
+
<pre>statgen-setup launch --tutorial plink
 
</pre>
 
</pre>
  
 +
Alternatively, you can opt to run the exercise via command terminal from docker image provided,
 +
 +
<pre>statgen-setup login --tutorial plink
 +
</pre>
  
 
==Homozygosity Mapper==
 
==Homozygosity Mapper==
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* [https://github.com/statgenetics/statgen-courses/blob/master/handout/IGV.docx IGV exercise <nowiki>[DOCX]</nowiki>]
 
* [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)]
 
* [http://statgen.us/files/igv_exercise.zip Exercise files (VCF and BAM)]
 +
  
  
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</pre>
 
</pre>
  
 +
==LD clumping==
 +
* [https://github.com/cumc/bioworkflows/blob/master/GWAS/LD_Clumping.ipynb LD Clumping Exercise <nowiki>[IPython Notebook]</nowiki>]
 +
 +
 +
To run the exercise from docker image provided,
 +
 +
<pre>statgen-setup launch --tutorial clumping
 +
</pre>
 +
 +
==MR-JTI for TWAS==
 +
* [https://github.com/statgenetics/statgen-courses/blob/master/notebooks/MR_JTI.ipynb MR-JTI Exercise <nowiki>[IPython Notebook]</nowiki>]
 +
 +
 +
To run the exercise from docker image provided,
 +
 +
<pre>statgen-setup launch --tutorial twas
 +
</pre>
  
 
==Pleiotropy==
 
==Pleiotropy==
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<pre>statgen-setup launch --tutorial pseq
 
<pre>statgen-setup 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>
 +
 +
 +
 +
==R and PLINK==
 +
 +
To run the exercise from docker image provided,
 +
 +
<pre>statgen-setup launch --tutorial plink-r-nothnagel
 
</pre>
 
</pre>
  
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to load the data-set to the JupyterLab workspace.
 
to load the data-set to the JupyterLab workspace.
 +
  
  

Latest revision as of 16:06, 8 November 2022

Running Tutorials on Your Computer

Starting Fall 2019 we adopt docker to run our course material . We have created various docker repositories with source material freely available from 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

Preparing Your Computer

Linux
Mac
Windows

Running Exercises

Tutorial specific instructions

We use a script "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. Command "statgen-setup login" will allow you to start and login to a Linux command line environment (regardless of your current computational environment) to perform all analysis in command shells. This works for all the tutorials on this page. Additionally, some tutorials support command "statgen-setup launch" which will start a JupyterLab server to perform the analysis.

Alohomora

Annovar complex traits

To run the exercise from docker image provided, 

statgen-setup login --tutorial annovar

Annovar Mendelian traits

Cochran Armitage Trend Test


Epistasis (PLINK and CASSI)

To run the exercise from docker image provided, 

statgen-setup login --tutorial epistasis


FastLMM

To run the exercise from docker image provided, 

statgen-setup login --tutorial fastlmm-gcta


Fine-mapping (SuSiE method)


To run the exercise from docker image provided, 

statgen-setup launch --tutorial finemap

GCTA

To run the exercise from docker image provided, 

statgen-setup login --tutorial fastlmm-gcta


Gemini

To run the exercise from docker image provided, 

statgen-setup login --tutorial gemini


Genehunter


To install from packages, follow the configuration steps above and run the following command. 

sudo apt-get install genehunter-tutorial

The exercise's files will then be installed in the folder /home/shared/genehunter. You can run from there or copy the files into your user's home directory and proceed with the exercise.

GWAS: Data Quality Control

To run the exercise via JupyterLab from docker image provided, 

statgen-setup launch --tutorial plink

Alternatively, you can opt to run the exercise via command terminal from docker image provided, 

statgen-setup login --tutorial plink

GWAS: Association Analysis Controlling for Population Substructure

To run the exercise via JupyterLab from docker image provided, 

statgen-setup launch --tutorial plink

Alternatively, you can opt to run the exercise via command terminal from docker image provided, 

statgen-setup login --tutorial plink

Homozygosity Mapper

IGV


Linkage/FastLinkage


To run the exercise from docker image provided, 

statgen-setup login --tutorial mlink

LD clumping


To run the exercise from docker image provided, 

statgen-setup launch --tutorial clumping

MR-JTI for TWAS


To run the exercise from docker image provided, 

statgen-setup launch --tutorial twas

Pleiotropy

To run the exercise from docker image provided, 

statgen-setup login --tutorial pleiotropy


Polygenic risk prediction (NPS method)

To run the exercise from docker image provided, 

statgen-setup login --tutorial nps


Polygenic risk prediction (LDpred2 method)


To run the exercise from docker image provided, 

statgen-setup launch --tutorial ldpred2

Then follow prompts on the terminal output to open up the JupyterLab server in your web browser. If it is the first time you start this server, please open a command terminal inside JupyterLab, and type 

get-data

to load the data-set to the JupyterLab workspace.


Population Genetics


To run the exercise from docker image provided, 

statgen-setup login --tutorial popgen


PSEQ

To run the exercise from docker image provided, 

statgen-setup launch --tutorial pseq

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, 

statgen-setup login --tutorial pseq


R and PLINK

To run the exercise from docker image provided, 

statgen-setup launch --tutorial plink-r-nothnagel


REGENIE


To run the exercise from docker image provided, 

statgen-setup launch --tutorial regenie

Then follow prompts on the terminal output to open up the JupyterLab server in your web browser. If it is the first time you start this server, please open a command terminal inside JupyterLab, and type 

get-data

to load the data-set to the JupyterLab workspace.


Regression

To run the exercise from docker image provided, 

statgen-setup login --tutorial regression


RV-TDT

Installing Packages

To install from packages, follow the configuration steps above and run the following command. 

sudo apt-get install rvtdt-tutorial

The exercise's files will then be installed in the folder /home/shared/rvtdt. You can run from there or copy the files into your user's home directory and proceed with the exercise.

SEQLinkage


To install from packages, follow the configuration steps above and run the following command. 

sudo apt-get install seqlinkage-tutorial

The exercise's files will then be installed in the folder /home/shared/seqlinkage. You can run from there or copy the files into your user's home directory and proceed with the exercise.

SEQSpark

Installing Packages

To install from packages, follow the configuration steps above and run the following command. 

sudo apt-get install seqspark-tutorial

The exercise's files will then be installed in the folder /home/shared/seqspark. You can run from there or copy the files into your user's home directory and proceed with the exercise.In order for the commands to work correctly, you don't need to reboot, but you should log out and log back in to make sure that the computer's environment is correctly configured.

SLINK

To run the exercise from docker image provided, 

statgen-setup login --tutorial slink

SUPERLINK

Variant Association Tools


To run the exercise from docker image provided, 

statgen-setup launch --tutorial vat

Then follow the prompts on the terminal output to open up the JupyterLab server in your web browser. You should find the exercise notebook in the side panel, and you can click to open it.

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