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Achievement: StarstruckAchievement: YOLOAchievement: Pair ExtraordinaireAchievement: Arctic Code Vault ContributorAchievement: Pull Sharkx3

Achievements

Achievement: StarstruckAchievement: YOLOAchievement: Pair ExtraordinaireAchievement: Arctic Code Vault ContributorAchievement: Pull Sharkx3

Organizations

@tatonetti-lab @hetio

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zietzm/README.md

Introduction 👋

Hi there! I'm Michael Zietz. I'm a data scientist and genetics researcher, focused on developing new statistical and machine learnings methods with applications in healthcare and biomedicine. 🧬 I'm currently a Research Data Scientist at Cedars-Sinai Computational Biomedicine. Previously, I did my PhD at Columbia University DBMI and studied Physics at Penn, where I did research on heterogeneous networks in the Greene Lab. 🕸️ I'm interested in methods development, reproducible research, and accelerating the pace of scientific progress on complex diseases. 🏥

💡 Some projects

WebGWAS: Instant, free, online genome-wide association studies (GWAS)

MaxGCP: Optimal phenotyping for research in complex disease genetics (code, analysis)

COVID Blood type: Study of the relationship between ABO type and COVID-19 (analysis, paper, New York Times)

XSwap: A fast implementation of degree-preserving network randomization (code, analysis, paper)

Other tools 🔨

  • sumher_rs: Efficiently estimating a genetic covariance matrix using SumHer (code)
  • mdav: Data anonymization tool implementing maximum distance to the average vector (MDAV) anonymization (code)
  • pymbend: Bending matrices to be positive semi-definite (code)
  • Micromanubot: A user-friendly build tool for academic preprints in LaTeX (code)
  • OnsidesDB.org: Interactive exploration of adverse drug events extracted using large language models (code)

Pinned Loading

  1. tatonetti-lab/webgwas-backend tatonetti-lab/webgwas-backend Public

    WebGWAS: Instant, free online genome-wide association studies. Server backend code.

    Rust 1

  2. tatonetti-lab/indirect-gwas tatonetti-lab/indirect-gwas Public

    Fast GWAS on linear combinations of traits using only summary statistics

    Rust 6

  3. tatonetti-lab/maxgcp tatonetti-lab/maxgcp Public

    Maximum genetic component phenotyping. An advanced method for defining observational phenotypes using genetic information.

    Python 2

  4. hetio/xswap hetio/xswap Public

    Python library (C++ backend) for degree-preserving network randomization

    C 12 3

  5. sumher_rs sumher_rs Public

    Heritability and genetic correlation from GWAS. Wrapper around LDAK for fast parallel computation

    C 5 1

  6. webgwas-analysis webgwas-analysis Public

    Figures and analysis for the WebGWAS project paper

    Jupyter Notebook