Single cell RNA Sequencing Analysis

Used for filtering, normalization, scaling, integration (optionally), and clustering of single or aggregated single-cell RNA-Seq datasets

The main functional blocks of sc-rna-analyze-wf.cwl workflow are shown below. For detailed workflow structure refer to CWL Viewer.

---

To reproduce the analysis of single-cell RNA sequencing data described in the Surumbayeva, Kotliar et al., 2021 paper make sure you have cwltool, Docker, Git and wget tools installed. Then proceed to the following steps.

1. Create a temporary folder and clone the current repository.

   mkdir sc_rna
   cd sc_rna
   git clone https://github.com/Barski-lab/sc-seq-analysis.git
   

2. Create a folder for input data. Download required input files from the Figshare either using a web browser or commands below.

   mkdir inputs
   cd inputs
   wget -O filtered_feature_bc_matrix.tar.gz https://figshare.com/ndownloader/files/34819513
   wget -O aggregation.csv https://figshare.com/ndownloader/files/34819516
   wget -O condition.csv https://figshare.com/ndownloader/files/34819519
   wget -O mouse_cell_cycle_genes.csv https://figshare.com/ndownloader/files/34822054
   

3. Copy the job definition file into the inputs folder.

   cp ../sc-seq-analysis/jobs/sc-rna-analyze-wf.yaml .
   

4. Create a folder for workflow outputs and execute sc-rna-analyze-wf.cwl workflow with sc-rna-analyze-wf.yaml job definition file.

   cd ..
   mkdir outputs
   cd outputs
   cwltool ../sc-seq-analysis/workflows/sc-rna-analyze-wf.cwl ../inputs/sc-rna-analyze-wf.yaml
   

Step 1. Filters single-cell RNA-Seq datasets based on the common QC metrics.

Raw	Filtered

Step 2. Integrates multiple single-cell RNA-Seq datasets, reduces dimensionality using PCA.

Step 3. Clusters single-cell RNA-Seq datasets, identifies gene markers.