Rheumatoid Arthritis project. single cell RNA sequencing data.
Softwares:
- CellRanger v.2.2.0 source: 10XGenomics, https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest platform: Linux system(8-core Intel or AMD processor (16 cores recommended); 64GB RAM (128GB recommended); 1TB free disk space;64-bit CentOS/RedHat 6.0 or Ubuntu 12.04) typical install time: 12h
- Seurat v3.1.1 (Butler et al., 2018; Stuart et al., 2019). source: https://satijalab.org/seurat/v3.1/ platform: R, install by "install.packages(Seurat)"
- clusterProfiler v3.12.0 (Yu et al., 2012) source: https://guangchuangyu.github.io/software/clusterProfiler/ platform: R, install by "BiocManager::install(clusterPfrofiler)"
- DAVID 6.8 (Huang et al., 2009a, b) source: https://david.ncifcrf.gov/,online tool,following official structions.
- Monocle3 (Cao et al., 2019; Qiu et al., 2017a; Qiu et al., 2017b; Trapnell et al., 2014). source: https://cole-trapnell-lab.github.io/monocle3/ platform:R, install by
- CellPhoneDB v2.1.2 (Efremova et al., 2020; Vento-Tormo et al., 2018) source: https://www.cellphonedb.org/ platform: Python, install by "pip install CellPhoneDB"
Scripts: 01 cellranger.sh single cell RNA-seq data alignment using CellRanger output: expression matrix of each sample
02 merge-individual sample.R merge all individual Seurat objects from the same tissue (PBMC or synovial tissue)
03 extract-major celltype.R extract major cell types from PBMC and SM.
04 DE_and_enrich_test.R find differential genes and do enrich test;calculate module score.
05 Seurat-Monocle3.R using Monocle3 to do trajectory analysis
06-1 samples_prepaired-cellphoneDB.R prepare data for cellphoneDB
06-2 cellphoneDB.sh predict cell-cell interaction using cellphoneDB.