Software & data

Built for discovery.
Shared for everyone.

Open tools, reproducible analyses and datasets that help the research community ask new questions.

Software & analysis

Lee Lab on GitHub

Python, Jupyter

PsychADxD

Analysis code behind the PsychAD cross-disorder atlas (Nature, 2026).

Lee Lab and CDN

Code Paper

Python · MIT

scMyeloidAD

Analysis code for FreshMG, the human microglia and perivascular macrophage atlas (Nature Genetics, 2026).

Lee Lab

Code Paper

Python · GPL-3.0

STARRPeaker

Peak caller for STARR-seq enhancer assays, used to process ENCODE STARR-seq data.

Donghoon Lee (Gerstein Lab)

Code Paper

Python

ESPRNN

Predicts splicing from the epigenome with a recurrent neural network.

Donghoon Lee (Gerstein Lab)

Code Paper

Python

MotifTools

Scores how variants break or create transcription factor motifs, and motif burden across regions.

Donghoon Lee

Code

Python

SCTools

Helpers for Pegasus and Scanpy, including on-disk AnnData for atlases that don't fit in memory.

Donghoon Lee

Code

Python · GPL-3.0

ssq

Super simple queue. Turns a list of commands into an LSF job array on Minerva and emails you when it's done.

Lee Lab

Code

Explore the data

A foundation for new questions.

PsychAD atlas on CELLxGENE

Browse the cross-disorder atlas in your web browser. Open access.

PsychAD on the AD Knowledge Portal

Raw and processed single-nucleus data and metadata (controlled access).

FreshMG on Synapse

FreshMG single-cell data and metadata, through the AD Knowledge Portal.

psych-ad.org

The PsychAD consortium site, with data access and companion studies.

From our collaborators

A shared toolkit

R / Bioconductor

dreamlet

Pseudobulk differential expression for cohort-scale single-cell data with linear mixed models.

Gabriel Hoffman (CDN)

R / Bioconductor

crumblr

Tests for changes in cell-type composition across the cell lineage tree.

Gabriel Hoffman (CDN)

Python

PASCode

Scores single cells for association with a clinical phenotype using graph neural networks.

Daifeng Wang Lab

Python

iBrainMap

Builds a personal gene-regulatory and cell-cell interaction network for each donor.

Daifeng Wang Lab

Earlier tools & contributions

RADAR — Variant annotation for RNA-binding protein regulomes (co-developer)
DECODE — Deep learning for enhancer boundaries
SCAN-ATAC-Sim — Single-cell ATAC-seq simulator
TopicNet — Regulatory network change with topic models
NIMBus — Mutation burden analysis