Resources

  • Research Groups

    Overview of spatial technologies

    (Please email me if you suggest any new groups not listed here)

  • Seminar Series

    Spatial omics (Organized by Drs. Rong Fan and Ahmet Coskun)
    Single cell genomics (Organized by Dr. Rahul Satija)
    Spatial Biology Summit (Organized by Dr. Mike Angelo)
    Spatial Biology (Nature Conferences)

  • Protocols

    Spatial sequencing (DBiT-seq)

    Single-cell co-seq of mRNA and open chromatin (SHARE-seq)

    Spatial Metabolomics Protocols

    Single cell epigenetics (Cut&Tag)

  • Computational Methods

    Cell Type Deconvolution
    Spatial and Single-Cell Data Integration
    RNA Velocity
    Toolbox for ATAC-seq

  • Reference Database

    snATAC-seq Human Tissue

    Motif Database

    Mouse brain atlas by MERFISH

  • Growing Up in Science

    Life and career stories of scientists

    Night science about creativity

    Becoming a resilient scientist

    Productivity

    Mentorship and lab culture

Spatial Transcriptomics/Genomics (Imaging-based)

Xiaowei Zhuang, Harvard [web] Tech: MERFISH [Company: Vizgen]

Long Cai, Caltech [web] Tech: SeqFISH [Company: Spatial Genomics]

Xiao Wang, Broad Institute [web] Tech: STARmap , RIBOmap

Spatial Transcriptomics/Genomics (Next Generation Sequencing-based)

Joakim Lundeberg, KTH Royal Institute of Technology [web] Tech: Spatial Transcriptomics [Company: 10x Genomics]

Fei Chen, Broad Institute [web] Tech: Slide-seqV2 [Company: Curio Bioscience]

Jun Hee Lee, Univ. of Michigan [web] Tech: Seq-Scope

Liangcai Gu, U Washington [Web] Tech: Pixel-seq

Jian Wang, Beijing Genomics Institute, Tech: Stereo-seq [Company:BGI]

Spatial Proteomics

Garry Nolan, Stanford [web] Tech: CODEX [Company: Akoya Biosciences]; MIBI [Company: Ion Path]

Michael Angelo, Stanford [web] Resource: MIBI-database

Bernd Bodenmiller, University of Zurich [web] Tech: Imaging mass cytometry (IMC) [Company: Hyperion]

Peter Sorger, Harvard Medical School [web] Tech: CyCIF

Peng Yin, Harvard [web] Tech: Immuno-SABER [Company: Ultivue]

Spatial Metabolomics

Theodore Alexandrov, EMBL [web] Tech: SpaceM

Spatial Multi-Omics

Rong Fan, Yale [web] Tech: DBiT-seq, Spatial ATAC-seq, Spatial Cut&Tag, Spatial CITE-seq [Company: AtlasXomics]

Sanja Vicković, New York Genome Center, Columbia [web] Tech: HDST, SM-Omics

Joseph M. Beechem, Nanostring [web] Tech: GeoMx DSP , CosMX [Company: Nanostring]

Ahmet F. Coskun, Georgia Tech [web] Tech:seqFISH, Super-Res. MIBI/CODEX

Research Groups

Seminars

Spatial Omics Seminar Series, Organized by Prof. Rong Fan and Prof. Ahmet F. Coskun (Georgia Tech). Replays available on Youtube.

Single Cell Genomics Day, Organized by Prof. Rahul Satija (New York Genome Center; NYU).

Spatial Biology Summit, Organized by Prof. Mike Angelo (Stanford University)

Spatial Biology - A technology symposium, Organized by Nature Conferences, Oct 29, 2024.

Protocols

Spatial Platform Set-up

Barcoding tissue with spatial information using microfluidics (DBiT-seq)
Spatial multi-omics sequencing for fixed tissue via DBiT-seq, Su G, Qin X, Enninful A, Bai Z, Deng Y, Liu Y, Fan R, Star Protocols, DOI: 10.1016/j.xpro.2021.100532. (2021)

Library Construction

Single cell joint profiling of chromatin accessibility and gene expression at scale
SHARE-seq V1 step-by-step protocol, Ma S, Regev A, Buenrostro J, DOI: 10.17504/protocols.io.bmbik2ke. (2021)

Evaluation of Spatial Metabolomics Protocols

Spatial metabolomics using imaging mass spectrometry (MS) , label-free, 24 MALDI-imaging MS protocols evaluated
Large-Scale Evaluation of Spatial Metabolomics Protocols and Technologies, Saharuka V et al., BioRXiv, DOI: 10.1101/2024.01.29.577354. (2024)

Single Cell Cut&Tag for Chromatin Modification

Single cell Cut&Tag Protocol , Bartosovic M, Kabbe M, and Castelo-Branco G, Nature Biotech, 2021.

Multi-omic nanoCut&Tag Protocol (up to three epigenomic modalities at single-cell resolution using nanobody-Tn5 fusion proteins) Bartosovic M and Castelo-Branco G, Nature Biotech, 2023.

Computational Methods

Cell Type Deconvolution

cell2location
Omer Bayraktar, Wellcome Sanger Institute [web] [Tutorial]
Oliver Stegle, German Cancer Research Center (DKFZ) & European Molecular Biology Laboratory (EMBL) [web]

destVI
Nir Yosef, Weizmann Institute [web]

RCTD
Fei Chen, Broad Institute; Rafael A. Irizarry, Dana-Farber Cancer Institute, Harvard. [GitHub]

Spatial and Single-Cell Data Integration

Seurat
Rahul Satija, New York Genome Center, New York Univ. [web]

MaxFUSE : CODEX spatial proteome data + scRNA-seq
Zongming Ma, Yale [web]; Nancy Zhang, UPenn [web]; Garry Nolan, Stanford [web]

SpatialGlue : integrate spatial mRNA-seq and spatial ATAC-seq
Jinmiao Chen, Agency for Science, Technology and Research (A*STAR), Singapore [web]

iStar : histology images + spatial RNA-seq, a vision transformer to extract features from images
Mingyao Li, UPenn [web]

Tangram
Tommaso Biancalani and Aviv Regev, Broad Institute [GitHub]

RNA Velocity

Velocyto (steady state model)
Sten Linnarsson, Karolinska Institutet; Peter V. Kharchenko, Harvard [Tutorial]

scVelo (static and dynamic model)
F. Alexander Wolf and Fabian J. Theis, Technical University of Munich [Tutorial]

ATAC-Seq

ArchR (single cell ATAC analysis)
Jeffrey M. Granja, William J. Greenleaf, Stanford University [Tutorial]

SnapATAC2 (single cell ATAC analysis)

Bing Ren, University of California, San Diego [web] [Tutorial]

Benchmarking different spatial/single-cell methods

Benchmarking the computational methods (Li et al., Nature Methods, 2022.)

Systematic comparison of sequencing-based spatial transcriptomic methods (You et al., BioRXiv, 2023)

Comparative analysis of multiplexed in situ gene expression profiling technologies (Hartman A and Satija R, BioRXiv, 2024)

Reference Database / Web Tool

Brain MRI and Histology Atlas

NextBrain: a next-gen probabilistic atlas of the human brain with 333 regions.
Juan Eugenio Iglesias, Harvard [web]

Allen Brain Atlas: reference brain anatomy atlas of the human and mouse brains. Our favorite region of the brain is hippocampus.
Allen Institute

HuBMAP

Human BioMolecular Atlas Program (HuBMAP): single-cell mRNA reference data. 31 organs from 213 donors, leading to now 1841 samples and 2332 datasets across the three main modalities.

Chan Zuckerberg CELL by GENE Discover

Human single cell data portal organized by the Chan Zuckerberg Biohub. To date, 85 Million cells from 1285 datasets have been included. A quick check for which cell type expresses which genes.

Mouse Brain Atlas by MERFISH and scRNA-seq

Allen Brain Cell Atlas Coronal sections of mouse brain slices were profiled with MERFISH (400 genes) and scRNA-seq (4 million cells).

snATAC-seq

Cis Element Atlas : Reference snATAC data from human brain / heart, mouse brain
Bing Ren, University of California, San Diego [web]

Motif Database Quick Look

Non-redundant TF motif database : 286 distinct motif clusters out of >2000 motif models. A quick check for similar motif sequences. [Model explanation]
Jeff Vierstra, Altius Institute for Biomedical Sciences [web]

Motif Database Web Tool

HOCOMOCO : HOmo sapiens COmprehensive MOdel COllection (HOCOMOCO) provides 1443 transcription factor (TF) binding models including secondary motif subtypes for 949 human TFs and 720 mouse orthologs. Quick check for the motif sequence of a specific transcription factor.
Ivan V Kulakovskiy, Vavilov Institute of General Genetics [web]

Motif Database Web Tool - Multi Species

JASPAR : Quick check for the motif sequence of a specific transcription factor.
Anthony Mathelier, University of Oslo [web]

Growing Up in Science

Life and career stories of scientists

An unofficial series of personal narratives from scientists, organized by New York University. Wei Ji Ma said, ‘Smooth and straight career paths are rare.” The talks focus on the life and career story with an emphasis on struggles, doubts, failures, and detours. I rate this as the best seminar series for building mental supportive system in scientific community.

Night Science

Podcasts and learning materials organized by Dr. Itai Yanai (New York University). A great series about the origin of creativity.

Becoming a resilient scientist

Seminars and tutorials organized by NIH Office of Intramural Training & Education.

Productivity

Cohen, Carl M.; Cohen, Suzanne L (2018), Lab Dynamics: Management and Leadership Skills for Scientists, Cold Spring Harbor Laboratory Press.

Mentorship and Lab Culture

Resources compiled by NYU

Research Pioneers

Sai Ma - Icahn School of Medicine at Mount Sinai - Single-Cell Epigenetics

John Hickey - Duke University - Spatial Omics of Cell Therapy

Zhi Huang - Stanford University- Digital Pathology

Avi Ma'ayan - Icahn School of Medicine at Mount Sinai - Computational Tools for Gene Regulatory Networks

Michael Snyder - Stanford University- Gene Regulatory Networks

Itai Yanai - New York University - Evolutionary Biology in Cancer, Night Science Podcast