Brings bulk and pseudobulk transcriptomics to the tidyverse

Seurat meets tidyverse. The best of both worlds.

R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)

A tidyverse suite for (pre-) machine-learning: cluster, PCA, permute, impute, rotate, redundancy, triangular, smart-subset, abundant and variable features.

🔜 Integrative Toolbox of Word Embedding Research for Psychological Science.

Project Dense Vectors Text Representation on 2D Plan

Stochastic Neighbor Embedding Experiments in R

SNE Simulation Dataset Functions

R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.

Feature engineering in machine learning

Cytometry analysis pipeline for large and complex datasets (CAPX) (beta)

Display gene expression along a given reduced dimension on a heatmap

Plot_ly-based plotting functions for use with Seurat objects

An R package for t-SNE (t-Distributed Stochastic Neighbor Embedding)

A project experimenting with implementing clustering algorithms in R

Data Understanding using- PCA, LDA, tSNE, and UMAP.

Public data for the Embedding Projector