chanwkimlab

MarcoPolo

MarcoPolo is a clustering-free approach to the exploration of bimodally expressed genes along with group information in single-cell RNA-seq data

GAT

GAT (Generic Genome-Wide Association Tool)

MHC_Kor_Assoc

Phenome-wide association study of the major histocompatibility complex region in the Korean population identifies novel association signals

regional_heritability_analysis

Regional Heritability Analysis is a software package for estimating regional heritability of small genomic segments.

UveitisJIA_MHC-fineMapping

Scripts and data used in analyses for "An amino acid motif in HLA-DRβ1 distinguishes patients with uveitis in juvenile idiopathic arthritis." Preprint: https://www.biorxiv.org/content/early/2017/08/14/140954

academic-kickstart

attributionpriors

Tools for training explainable models using attribution priors.

basenji

Sequential regulatory activity predictions with deep convolutional neural networks.

breakout_game

noncoding_pytorch

chanwkimlab

Config files for my GitHub profile.

CLAM

Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

cse512_final

dart-fss-example

dart-fss-example

DEEP-HLA

Upload test

dsd_termproject

DuoClustering2018

R package with data sets and clustering results from Duò et al (F1000Research 2018)

dynamic-cell-classifier

fastshap

An amortized approach for calculating local Shapley value explanations

hess

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

ldsc

LD Score Regression (LDSC)

path_explain

A repository for explaining feature attributions and feature interactions in deep neural networks.

PyDeepSEA

DeepSEA implements in PyTorch

scDD

R package to identify genes with differential distributions in single-cell RNA-seq

scde

R package for analyzing single-cell RNA-seq data

shap

A game theoretic approach to explain the output of any machine learning model.

Transformer-Explainability

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

treeexplainer-study

Code and documentation for experiments in the TreeExplainer paper

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

vit-shapley