KrishnaswamyLab/phateR

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KrishnaswamyLab/phateR

KrishnaswamyLab

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PHATE dimensionality reduction method implemented in R

PHATE

PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.

MAGIC

MAGIC (Markov Affinity-based Graph Imputation of Cells), is a method for imputing missing values restoring structure of large biological datasets.

Jupyter Notebook

SAUCIE

TrajectoryNet

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

Jupyter Notebook

SingleCellWorkshop

Jupyter Notebook

scprep

A collection of scripts and tools for loading, processing, and handling single cell data.

ReLSO-Guided-Generative-Protein-Design-using-Regularized-Transformers

a Transformer-based neural network for generating highly optimized protein sequences called Regularized Latent Space Optimization (RELSO)

Jupyter Notebook

Multiscale_PHATE

Creating multi-resolution embeddings and clusters from high dimensional data

Jupyter Notebook

travelgan

graphtools

Tools for building and manipulating graphs in Python

DiffusionEMD

Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings

Jupyter Notebook

AAnet

Archetypal Analysis network (AAnet)

Jupyter Notebook

TPHATE

MAGAN

MIOFlow

Jupyter Notebook

phemd

Identifying cell subpopulational differences among single-cell biospecimens

PECAN

PECAN: Persistent Condensation

Jupyter Notebook

SUGAR

Synthesis using Geometrically Aligned Random-walks

CATCH

Learning cellular hierarchy from scRNAseq data

Jupyter Notebook

GSAE

Code from 'Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings"

Jupyter Notebook

HeatGeo

Embedding with the Heat-geodesic dissimilarity

Jupyter Notebook

visualization_selection

Selecting the right tool for the job: understanding drawbacks and biases in visualization methods

Jupyter Notebook

LearnableScattering

Learnable Geometric Scattering Network

CUTS

[MICCAI 2024] CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation

LAD

Lipschitz Anomaly Discriminator

logicml

CurveNet

Diffusion curvature and Hessian prediction using point samples from quadratic hypersurfaces

Cell-Dynamics-Pipeline

scgraph

Graph-based methods for the analysis of single-cell data

ImageFlowNet

GeoSinkhorn

Code for the paper Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds.

GSPA-manuscript-analyses

Learning meaningful representations of genes

Jupyter Notebook

Gene-Signal-Pattern-Analysis

Learning meaningful representations of genes

Jupyter Notebook

graph_fit

New ways of fitting a graph to vector data.

Jupyter Notebook

pointcloud_scattering

scnn

Deep learning methods for the analysis of single-cell data

Trellis

NN-LossLandscape-PHATE

Exploring the Geometry and Topology of Neural Network Loss Landscapes

CSHL_ComputationalGenomics2022

Directed-Hierarchical-Gene-Networks

scMMGAN

RiTINI

Regulatory Temporal Interaction Network Inference

spARC

Denoising spatial transcriptomics data

Jupyter Notebook

GEFMAP

Jupyter Notebook

CSHL_ComputationalGenomics2023

krishnaswamy-lab-site

phate-docker

Interactive command line docker script for running PHATE

NSCLC_pembro_sbrt

Jupyter Notebook

GRASSY-Net

NeuronTransform

FMGAN

Condensation

Diffusion Condensation is a topologically-inspired machine learning algorithm that is used to identify populations of cells across granularities.

Jupyter Notebook