stephenslab Goto Github PK
Name: Stephens lab
Type: Organization
Bio: Research in statistical and computational methods for genetics at the University of Chicago.
Name: Stephens lab
Type: Organization
Bio: Research in statistical and computational methods for genetics at the University of Chicago.
Code and analyses from "FDR: A New Deal" paper
Docker image for adaptive shrinkage paper
Workflow template
List of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
website for causal TWAS project
For discussing work related to confounding vs polygenicity
Correlation motif model.
Code and data reproducing results from our PLOS Genetics paper "Visualizing the structure of RNA-seq expression data using grade of membership models"
R code for simple and fast k-fold cross-validation.
A few illustrations of the daarem method.
R package for Dirichlet adaptive shrinkage and smoothing
slides for DDD site visit
Repo for Dynamic Statistical Comparisons project
DSC benchmark for Bayesian linear models.
DSC for comparing fine-mapping methods.
DSC for comparing accuracy of linear regression methods in prediction.
dsc to compare approaches to estimating/testing log-fold-change from counts
repo for dynamic statistical comparison of normal means methods
Application of DSC2 framework to a range of regression models.
dynamic statistical comparison of nonparametric regression (smoothing) methods, data with gaussian errors
Documents / write-up introducing dynamic statistical comparison
Companion code repository for the paper, "Fine-mapping from summary data with the Sum of Single Effects model".
Source code implementing Gaussian denoising simulations for Xing & Stephens (2016).
R package for Empirical Bayes thresholding and related methods.
Work on possible extensions to ebayesthresh—see stephenslab/ebayesthresh.
R package for Empirical Bayes thresholding and related methods
software for detecting hybrids, accounting for genotyping error and allelic dropout
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.