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:

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