Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).

A deep learning architecture for robust inference and accurate prediction of cellular dynamics

a scalable python suite for tree inference and advanced pseudotime analysis from scRNAseq data.

Characterize gene dynamics over trajectories using GLMs, GEEs, & GLMMs.

MiCV is a python dash-based web-application that enables researchers to upload raw scRNA-seq data and perform filtering, analysis, and manual annotation.

A composite regression neural network for latent timing prediction of single-cell RNA-seq data

Repository for benchmarking study of scRNA-Seq datasets for clustering and trajectory inference

Scripts for analysis of transcriptomic data of the developing cornea

my_RNA_seq_pipelines

Bioinfo scripts for the analyses described in EXPERIMENTAL PROCEDURES section of "Structured wound angiogenesis instructs mesenchymal barrier compartments in the regenerating nerve" manuscript

Implementation of MaSigPro for scRNA-Seq Data

TENET refined