YangLab@HKUST (YangLabHKUST)

YangLab@HKUST

YangLabHKUST

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Location:Hong Kong

Home Page:https://sites.google.com/site/eeyangc/

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YangLab@HKUST's repositories

STitch3D

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

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SpatialScope

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

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MR-APSS

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

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Portal

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

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DGLSB

Deep Generative Learning via Schrödinger Bridge

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XPASS

Cross-population analysis using GWAS summary statistics

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3DVesselSegNet

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

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mfair

mfair: Matrix Factorization with Auxiliary Information in R

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FLAG

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

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MATH-4432-Statistical-Machine-Learning

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

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MRAPSS_RealDataAnalysis_reproduce

R code for reproduce real data analysis in MRAPSS paper.

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SRT_alignment_and_integration

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

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VCM

R package VCM contains three approaches for solving variance components model: PX-EM algorithm, MM algorithm and Method of Moments

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VGrow-Pg

A tensorflow implementation of VGrow by using progressive growing method.

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XPA

Cross-population analysis using the individual-level GWAS data

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iGREX

Quantifying the impact of genetically regulated expression on complex traits and diseases

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LSMM

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

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scPI

scPI: A scalable framework for probabilistic inference insingle-cell RNA-sequencing data analysis

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BWMR

BWMR (Bayesian Weighted Mendelian Randomization)

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FIRM

Fast Integration of single-cell RNA-sequencing data across Multiple platforms

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LPM

Efficient statistical approach to characterize relationship among complex traits using summary statistics from multiple GWASs and functional annotations

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LPM-sim

Simulation codes to reproduce the results in the LPM paper

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LSMM-sim

Simulation codes and example to reproduce the results in the LSMM paper

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