Skip to content

Code for Zhang, Wei, Slowikowski, Fonseka, Rao, et al, Nature Immunology, 2019. Single-cell transcriptomics and proteomics data analysis and integration for rheumatoid arthritis synovial tissue. These integrative strategies can be generalized to any other diseases.

License

Notifications You must be signed in to change notification settings

fanzhanglab/amp_phase1_ra

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Use single-cell transcriptomics and proteomics to study Rheumatoid Arthritis (RA)

NIH Accelerating Medicines Partnership (AMP) Phase 1

Overview

This repo provides the Data availability, Source code, Website for our work on using single-cell transcriptomics and proteomics data to define inflammatory cell states in autoimmune disease - rheumatoid arthritis.

The published paper can be viewed and cited:

Zhang, F., Wei, K., Slowikowski, K., Fonseka, C.Y., Rao, D.A., et al. Defining Inflammatory Cell States in Rheumatoid Arthritis Joint Synovial Tissues by Integrating Single-cell Transcriptomics and Mass Cytometry. Nature Immunology, 2019.

Data availibility

The raw data of this study are available at:

Database Link with accession code Data type
ImmPort SDY998 single-cell RNA-seq, mass cytometry, bulk RNA-seq, flow cytometry, clinical and histology
dbGAP phs001457.v1.p1 single-cell RNA-seq and mass cytometry

Send us ([email protected] or [email protected]) an email if you have any quesitons or requests for data download.

Source code

Clone this repo:

cd ~/work/
git clone [email protected]:immunogenomics/amp_phase1_ra.git
cd amp_phase1_ra

Structure

The files in the repo are organized as follows:

.
├── R
|── data

data/ has Excel sheets with sample metadata and RData files with processed data ready for analysis.

R/ has code for analysis and creating figures:

  • Classify tissue samples using Mahalanobis distance: R/optimal_lymphocyte_threshold.R

  • Integrate bulk with single-cell RNA-seq: R/scRNAseq_bulkRNAseq_integrative_pipeline.R

  • Cluster and disease association test using mass cytometry: R/Tcell.SNE.densVM.server.R, R/Tcell.MASC.R

  • Identify cluster marker genes: R/cluster_marker_table.R, R/limma_differential_bulk.R

  • Functions for PCA, densisty analysis, etc: R/pure_functioins.R

  • Visualize results: R/cytof_results_plot.R, plot_cluster_markers.R, etc

  • More

Send us ([email protected]) an email if you have any quesitons for the analysis.

Website

Feel free to check out the websites and search your favorite genes:

  1. Shiny app: view single-cell RNA-seq, bulk RNA-seq, and mass cytometry data for rheumatoid arthritis data.
  2. UCSC Cell Browser: view single-cell RNA-seq datasets: 1 rheumatoid arthritis dataset and 2 lupus datasets.
  3. Broad Institue Single Cell Portal: view single-cell RNA-seq datasets: 1 rheumatoid arthritis datset and 2 lupus datasets.

For example, get everyting in one page using Shiny app:

drawing

Send us ([email protected], [email protected], or [email protected]) an email if you have any quesitons.

About

Code for Zhang, Wei, Slowikowski, Fonseka, Rao, et al, Nature Immunology, 2019. Single-cell transcriptomics and proteomics data analysis and integration for rheumatoid arthritis synovial tissue. These integrative strategies can be generalized to any other diseases.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published