Workshop: Julia Meets Mendel: Algorithms and Software for Modern Genomic Data Analysis

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We will introduce efficient computational methods in Julia for scalable genomic analysis. We will present genomic examples and offer simple hands on coding exercises via easy to use Jupyter notebooks as part of the OpenMendel project.

For more information, visit our Online Program Planner.

Learning Objectives:

  1. Compare the advantages of Julia programming over R or Python programming.
  2. Evaluate big genomic data within the OpenMendel package of Julia.
  3. Apply a variety of analyses on their laptops including ordinal GWAS, haplotyping and imputation, Linear Mixed Models, and Iterative Hard Thresholding (an alternative to Lasso for multivariate GWAS).
  4. Formulate a simple Julia programming script to suit their particular analysis or pipeline needs.

Key:

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Course Materials
Iterative Hard Thresholding in Genome-Wide Association Studies: Generalized Linear Models, Prior Weights, and Double Sparsity
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Ordered Multinomial Regression for Genetic Association Analysis of Ordinal Phenotypes at Biobank Scale
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Open to download resource.
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OpenMendel: A Cooperative Programming Project for Statistical Genetics
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Open to download resource.
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MM Algorithms for Variance Components Models
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Workshop Videos
01 - Open Mendel Overview
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02 - Biobank Application
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03 - Jupyter Notebooks Orientation
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04 - SnpArrays
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05 - Variance Components
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06 - Ordinal GWAS
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07 - Imputation
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08 - Ongoing work
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09 - Contribute to Open Mendel
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