# AI4All_Genomics

AI4All@Princeton is a summer camp that aims to promote diversity in computer science by teaching AI to young students of diverse backgrounds (https://ai4all.princeton.edu).  In this module, we will be investigating our genomic diversity by exploring natural genomic variation between world populations.

Relevant Links:

- IGSR home: Genohttp://www.internationalgenome.org/home

- Phase 3 1000 Genomes Results: https://www.nature.com/articles/nature15393#abstract

- Phase 3 1000 Genomes Data: https://ftp-trace.ncbi.nih.gov/1000genomes/ftp/release/20130502/

- Phase 3 1000 Genomes Processing Example: https://bitbucket.org/remills/1000gp_sv_phase3/src/master/

  - *** see gwas_sv_ld_filt_af.txt 

Data Preprocessing

- Run GATK software to subset SNPs: https://software.broadinstitute.org/gatk/documentation/tooldocs/4.0.0.0/org_broadinstitute_hellbender_tools_walkers_variantutils_SelectVariants.php

  - run ./gatk/gatk SelectVariants -V input.vcf -O output.vcf --keep-ids gwas_sv_ld_RSIDs.list 

    - example output.vcf: chrX_filtered.txt

 - concatenate vcf files using vcf-tools

  - https://vcftools.github.io/man_latest.html

Input Data:

 - "chr01-22_filtered.vcf"

  - to download: https://drive.google.com/drive/folders/1O7cRyGbEHrkjiCAkaKODN0V2HYTDXjss

To Do:

- Outline first two weeks

- Implement first two weeks notebooks (goals)

- start first 3 mini lectures

- plan (and test) which ML algorithms to introduce to students (clustering, standard prediction, etc)

- brainstorm intro slides to SNPs

- explore with python and benchmark runtimes

Files:

- 1000genomes_dataExploration.ipynb: preliminary exploration of 1000 Genomes data (PCA, SVM, data cleanup and filtering)