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On this page

  • Statistical/ML methods for genetics/genomics
    • Tools for inferring gene regulatory networks
    • Tools for genome-wide association studies
    • Tools for somatic variation analysis
    • Our methods development philosophy

Resources

Statistical/ML methods for genetics/genomics

Tools for inferring gene regulatory networks

  • LLCB : Our algorithm for inferring gene-regulatory networks from arrayed CRISPR perturbations with a bulk RNA-seq read-out.

Tools for genome-wide association studies

  • gwasplot : This is our in house R package for working with large-scale GWAS derived from WGS with many rare variants. It is very performant because it uses duckdb underneath.
  • UKB_regenie_workflow : This our workflow for running REGENIE in the UK Biobank DNA Nexus RAP. It is better than the ‘applet’ built into the platform.

Tools for somatic variation analysis

  • GEM : The genomic and epigenomic mutation rate estimator.
  • pileup_region : This was used to call U2AF1 mutatios in TOPMed.
  • PACER . This is the ‘official’ implementation of the variant calling procedure to quantify passenger mutations, which are the key ingredient of the Passenger-Approximated Clonal Expansion Rate (PACER).

Our methods development philosophy

We develop primarily in R/Python/Julia, with things trending more towards Julia. We aspire to write code that facilitates reproducible science. Practically, this means unit tests, documentation, Docker/Singularity images, and continuous integration (all of these facilitate reproducibility). We are increasingly adopting these principles into all of code bases that are in progress.

Copyright 2024, Josh Weinstock