PYangLab

AdaSampling

Package for positive unlabeled and label noise learning

Cepo

Uncovering cell identity genes using differential stability of expression in single cells.

ClueR

Cluster Evaluation R package (ClueR) for detecting key signaling events from time-series phosphoproteomics data

ESC-multiome

Multi-omic profiling reveals dynamics of the phased progression of pluripotency

KSP-PUEL

Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data

Matilda

Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-modality of such data and trains a neural network model to simultaneously learn multiple tasks including data simulation, dimension reduction, visualization, classification, and feature selection.

PhosR

PhosR is a package for the comprehensive analysis of phosphoproteomic data.

scCCESS

Single-cell Consensus Clusters of Encoded Subspaces

scDeepFeatures

Deep learning-based feature selection for single-cell omics data

SnapCCESS

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data

PYangLab/Matilda

Matilda is a multi-task framework for learning from single-cell multimodal omics data. Matilda leverages the information from the multi-modality of such data and trains a neural network model to simultaneously learn multiple tasks including data simulation, dimension reduction, visualization, classification, and feature selection.

PYangLab/PhosR

PhosR is a package for the comprehensive analysis of phosphoproteomic data.

PYangLab/scCCESS

Single-cell Consensus Clusters of Encoded Subspaces

PYangLab/AdaSampling

Package for positive unlabeled and label noise learning

PYangLab/Cepo

Uncovering cell identity genes using differential stability of expression in single cells.

PYangLab/ClueR

Cluster Evaluation R package (ClueR) for detecting key signaling events from time-series phosphoproteomics data

PYangLab/KSP-PUEL

Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data

PYangLab/scDeepFeatures

Deep learning-based feature selection for single-cell omics data

PYangLab/SnapCCESS

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data

PYangLab/SVGbench

Evaluating spatially variable gene detection methods for spatial transcriptomics data

PYangLab/SEGs

Identify stably expressed genes from single-cell RNA-seq data

PYangLab/scMultiBench

Multi-task benchmarking of single-cell multimodal omics integration methods

PYangLab/DeepMerge

PYangLab/PhosR_STAR_Protocols

PYangLab/SnapKin

PYangLab/TransOmicsData

A collection of trans-omic datasets

PYangLab/BioInfoSummer2015

PYangLab/ESC-multiome

Multi-omic profiling reveals dynamics of the phased progression of pluripotency

PYangLab/directPA

A package for pathway analysis in experiments with multiple perturbation designs.

PYangLab/dplyr

Plyr specialised for data frames: faster & with remote datastores

PYangLab/GeneticEnsemble

PYangLab/imbalanced-data-sampling

Automatically exported from code.google.com/p/imbalanced-data-sampling

PYangLab/imbalanced-data-sampling.image

Automatically exported from code.google.com/p/imbalanced-data-sampling.image

PYangLab/PAD

PAD (Proximal and Distal) clustering

PYangLab/PYangLab.github.io

Pengyi Yang Lab

PYangLab/ReFraction

A supervised machine learning approach for deterministic identification of MS-based proteome

PYangLab/rstan

RStan, the R interface to Stan

PYangLab/scNet

R package with collection of single cell RNA-sequencing (scRNA-seq) data analysis functions

PYangLab/self-boosted-percolator

Automatically exported from code.google.com/p/self-boosted-percolator

PYangLab/SPSs