Nan Xiao

Software

Python Packages
R Packages
VS Code Extensions
Web Applications
Machine Learning Workflows
Open Source Contributions
Awesome Lists
Hugo Themes

Python packages

  • tinytopics
    GPU-accelerated topic modeling via sum-to-one constrained neural Poisson NMF
    PyPI | GitHub
  • tinyvdiff
    Minimalist visual regression testing plugin for pytest
    PyPI | GitHub
  • py-pkglite
    A simple framework for packing source packages written in any programming language into a text file and restoring them into the original directory structure
    PyPI | GitHub
  • rtflite
    Lightweight RTF composer for Python
    PyPI | GitHub

R packages

Infrastructure and automation

Statistical machine learning

  • msaenet
    Multi-step adaptive estimation for sparse regressions
    CRAN | GitHub | Paper
  • stackgbm
    Minimalist implementation of model stacking for gradient boosted tree models built by xgboost, lightgbm, and catboost
    CRAN | GitHub
  • oneclust
    Maximum homogeneity clustering for univariate data
    CRAN | GitHub
  • logreg
    Regularized logistic regressions with computational graphs
    GitHub
  • OHPL
    Ordered homogeneity pursuit lasso for group variable selection
    CRAN | GitHub | Paper
  • RECA
    Relevant component analysis for supervised distance metric learning
    CRAN | GitHub
  • enpls
    Ensemble partial least squares regression
    CRAN | GitHub

Statistical graphics and computing

Bioinformatics and cheminformatics

VS Code extensions

Web applications

JavaScript apps

Shiny apps

Shiny apps, widgets, and templates for interactive data analysis.

Machine learning workflows

Open source contributions

  • gsDesign
    Group sequential clinical trial design, largely as presented in Jennison and Turnbull (2000)
    CRAN | GitHub | gsDesign: 15 Years of Development in 5 Minutes (4K 60fps)
  • gsDesign Shiny app
    Web application for group sequential clinical trial design
    Mirror 1 | Mirror 2
  • gsDesign2
    Group sequential design with non-constant effect
    CRAN | GitHub
  • simtrial
    Clinical trial simulation
    CRAN | GitHub
  • gMCPLite
    Lightweight fork of gMCP for graph-based multiple comparison procedures
    CRAN | GitHub
  • gMCPShiny
    Shiny app for graphical multiplicity control
    GitHub
  • r2rtf
    Create production-ready Rich Text Format (RTF) tables and figures
    CRAN | GitHub
  • metalite
    Unified data structure for metadata information in clinical analysis & reporting (A&R), leveraging the Analysis Data Model (ADaM) datasets for consistent and accurate metadata representation
    CRAN | GitHub
  • metalite.ae
    Analyzes adverse events in clinical trials using the metalite data structure. Simplifies the workflow to create production-ready tables, listings, and figures discussed in the adverse events analysis chapters of R for Clinical Study Reports and Submission.
    CRAN | GitHub
  • boxly
    Interactive box plot using plotly for clinical data analysis
    CRAN | GitHub
  • forestly
    Interactive forest plot for clinical trial safety analysis using metalite, reactable, plotly, and Analysis Data Model (ADaM) datasets
    CRAN | GitHub
  • PDXNet Portal
    Patient-derived xenograft (PDX) model, data, workflow, and tool discovery
    Paper
  • ashr
    Methods for adaptive shrinkage, using Empirical Bayes
    CRAN | Paper
  • dml
    Distance metric learning in R
    CRAN | Paper

Awesome lists and code recipes

  • awesome-shiny-extensions
    A curated list of R packages that offer extended UI or server components for Shiny
  • awesome-webr
    A curated list of awesome resources for learning WebR, a version of the statistical language R compiled for the browser and Node.js using WebAssembly
  • r-base-shortcuts
    A collection of lesser-known base R idioms and shortcuts for writing concise and fast base R code
  • r-rust-pkgs
    R packages using Rust on CRAN
  • r-future-recipes
    Guides and examples for the R future framework for parallel computing
  • r-windows-paths
    Key R toolchain paths for Windows systems
  • deep-learning-recipes
    R implementation for selected machine learning methods with deep learning frameworks
  • llm-cliches
    A collection of commonly used clichés and phrases in Large Language Models (LLMs) outputs.

Hugo/blogdown themes

Collections

Archives

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