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X.S.'s Projects

arae icon arae

tensorflow implementation of Adversarially Regularized Autoencoders (ARAE)

arae-1 icon arae-1

Code for the paper "Adversarially Regularized Autoencoders (ICML 2018)" by Zhao, Kim, Zhang, Rush and LeCun

cdmir icon cdmir

Causal Discovering, ModelIng and Reasoning

cevae icon cevae

Causal Effect Inference with Deep Latent-Variable Models

clomat icon clomat

CLoMAT: Conditional Logistic Model Association Tests. CLoMAT provides a general solution to control for population stratification by matching cases and controls based on their ancestry background.

depict icon depict

DEPICT code, instructions and an example

dsn icon dsn

Pytorch implementation of Domain Separation Networks

ensembl icon ensembl

The Ensembl Core Perl API and SQL schema

gemma icon gemma

Genome-wide Efficient Mixed Model Association

hdl icon hdl

High-definition likelihood inference of genetic correlations (HDL)

hess icon hess

Estimate local SNP heritability and genetic covariance from GWAS summary association statistics.

medltmle icon medltmle

R/medltmle: Estimation and Inference for Natural Mediation Effect in Longitudinal Data

models icon models

Models and examples built with TensorFlow

moss icon moss

(Model One-Step Survival): one-step TMLE for survival curve

npci icon npci

Non-parametrics for Causal Inference

polmm icon polmm

Proportional Odds Logistic Mixed Model (POLMM) for ordinal categorical data analysis

postgap icon postgap

Linking GWAS studies to genes through cis-regulatory datasets

spacox icon spacox

GWAS for survival analysis in large cohorts

spage icon spage

SaddlePoint Approximation implementation of GxE analysis

spatest icon spatest

Score Test Based on Saddlepoint Approximation

tybalt icon tybalt

Training and evaluating a variational autoencoder for pan-cancer gene expression data

uk_biobank_gwas icon uk_biobank_gwas

Overview of the data QC, code, and GWAS summary output from the 2017 UK Biobank data release

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