YangLabHKUST/UCS

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YangLabHKUST/UCS

YangLabHKUST

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Code for "UCS: a unified approach to cell segmentation for subcellular spatial transcriptomics"

STitch3D

Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices

SpatialScope

A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models

MR-APSS

Mendelian Randomization accounting for Pleiotropy and Sample Structure using genome-wide summary statistics

Portal

Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets

DGLSB

Deep Generative Learning via Schrödinger Bridge

XPASS

Cross-population analysis using GWAS summary statistics

LOG-TRAM

mfair

mfair: Matrix Factorization with Auxiliary Information in R

XMAP

3DVesselSegNet

hybrid representation learning approach for fully automatic and template-free vessel centerline extraction

Jupyter Notebook

PALM

FLAG

Flexible and Accurate Methods for Estimation and Inference of Gaussian Graphical Models with Applications

Jupyter Notebook

MRbenchmarking

MATH-4432-Statistical-Machine-Learning

Tutorials for MATH 4432 Statistical Machine Learning, HKUST, Fall 2023

XPA

Cross-population analysis using the individual-level GWAS data

MRAPSS_RealDataAnalysis_reproduce

R code for reproduce real data analysis in MRAPSS paper.

VGrow-Pg

A tensorflow implementation of VGrow by using progressive growing method.

SRT_alignment_and_integration

Measurement and comparison of several slices aligning methods and data integrating mathods for spatial transcriptomics data using several ST datasets.

LSMM

Efficient statistical approach to integrating functional annotations with genome-wide association studies