Resources
Quick Jump
Research Groups
Spatial Transcriptomics/Genomics
Spatial Proteomics
Spatial Metabolomics
Spatial Transcriptomics/Genomics
Joakim Lundeberg, KTH Royal Institute of Technology
Jun Hee Lee, Univ. of Michigan
Jian Wang, Beijing Genomics Institute
Spatial Multi-Omics
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 Groups That We Follow
Sai Ma - Icahn School of Medicine at Mount Sinai - Single-Cell Epigenetics
John Hickey - Duke University - Spatial Omics of Cell Therapy
Zhi Huang - University of Pennsylvania- AI-guided 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
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