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Computational tools for the Human Cell Atlas

A list of collaborative computational projects supported by CZI!

Here is a sample template you can copy and paste to add your project:

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
[name](link to repo) description of the project Jeremy Freeman, PhD @ CZI Science
[another project name](link to repo) description of the project Joe Hand and Danielle Robinson, PhD @ CS&S

Projects

Bioconductor

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
SingleCellExperiment R container for storing data from single-cell experiments Davide Risso @ Weill Cornell Medicine and Aaron Lun @ CRUK Camrbidge Institute
beachmat Provides a consistent R/C++ class interface for a variety of commonly used matrix types, including sparse and HDF5-backed matrices. Aaron Lun @ CRUK Camrbidge Institute

Cell Type

TITLE DESCRIPTION PEOPLE & AFFILIATIONS

Cell State

TITLE DESCRIPTION PEOPLE & AFFILIATIONS

Compression

TITLE DESCRIPTION PEOPLE & AFFILIATIONS

Imaging

TITLE DESCRIPTION PEOPLE & AFFILIATIONS

Latent Spaces

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
Tybalt Variational Autoencoder for Gene Expression (Paper) Greg Way, Qiwen Hu, and Casey Greene @Greenelab @Penn
PHATE Visualizing high-dimensional data (Paper) Kevin Moon, David van Dijk, and Smita Krishnaswamy @KrishnaswamyLab @Yale
CoGAPS Bayesian Non-Negative Matrix Factorization Elana Fertig, Genevieve Stein-O'Brien, and Tom Sherman @FertigLab
alevin Barcode correction, UMI deduplication and gene quantification for droplet-based scRNA-seq Avi Srivastava, Tom Smith, Ian Sudbery and Rob Patro @COMBINE-lab

Manifold Alignment

TITLE DESCRIPTION PEOPLE & AFFILIATIONS

Multiomics

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
CellBench Benchmark data for scRNA-seq Matt Ritchie, Luyi Tian @LuyiTian, WEHI
mixOmics paper A suite of latent component based methods encompassing different data integration frameworks (cross-platform, multi-omics) and feature selection Kim-Anh Le Cao@lecaolab, University of Melbourne
The Rosetta project: translating data across single-cell technologies to define human cell types Use parallel population-level mRNA & morphology data to uncover relationships between the two data types; test predictivity at a single-cell level Anne Carpenter, Juan Caicedo @CarpenterLab, Broad Institute

Population Variation

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
IA-SVA Iteratively Adjusted Surrogate Variable Analyses (Paper) Donghyung Lee @LeeLab, Anthony Cheng, Mohan Bolisetty, Duygu Ucar @UcarLab @JAX

Portals

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
ASAP Automated Single-cell Analysis Pipeline (Web portal) (Paper) Vincent Gardeux, Fabrice David, and Bart Deplancke @DeplanckeLab @EPFL
Xena Web-browser based integrative functional genomics data visualization (Web site) Brian Craft, Mary Goldman, Jing Zhu @ucscXena @UCSCXena

Scale

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
ADAM ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark and Parquet. Michael Heuer, Anthony Joseph, UC Berkeley; Ryan Williams, Uri Laserson, Icahn School of Medicine at Mount Sinai.

Trajectories

TITLE DESCRIPTION PEOPLE & AFFILIATIONS
STREAM STREAM is an interactive computational pipeline for reconstructing complex celluar developmental trajectories from sc-qPCR, scRNA-seq or scATAC-seq data (and soon scMethyl-Data!) Paper. We also provide an interactive website to compute and visualize trajectories and a database of precomputed trajectories: http://stream.pinellolab.org H Chen, L Albergante, JY Hsu, CA Lareau, GL Bosco, J Guan, S Zhou, AN Gorban, DE Bauer, MJ Aryee, DM Langenau, A Zinovyev, JD Buenrostro, GC Yuan, L Pinello @PinelloLab
traj-formats Traj-formats contains json-schema specifications for trajectory information. Collaborative effort from the trajectory community. Maintained by the @Stuart Lab at UCSC