PanKbase single cell map generation

This directory contains Code and docs for PanKbase islet single cell map analysis.

Content

1. 1_preprocessing:
   This directory contains Jupyter notebooks with details about how to execute code, along with scripts (R/Python/Snakemake).
   

• scripts: directory contains scripts to run analyses.
  
• 0_collecting_data.ipynb: Jupyter notebook with instructions on how data was downloaded.
  
• 1_run_processing_pipeline.ipynb: Jupyter notebook with instructions on how to run Nextflow pipeline to process scRNA-seq data.
  
• 2_barcode_qc.ipynb: Jupyter notebook with instructions on how to pull together multiple QC metrics, generate QC plots and choosing barcodes that likely correspond to cells.
  
• 2_python_req.yml: File with conda environment requirements to generate plots like in 3_barcode_qc.ipynb.
• 3_run_modifed_cellbender.R.ipynb: Jupyter notebook with instructions on how to set up pipeline to run Cellbender with modified settings.
  
• 4_HTODemux.R.ipynb: Jupyter notebook with instructions on how to analyze HTO data.
  

2. 2_doublet_detection/: This directory contains Jupyter notebooks with details about how to execute code, along with scripts (R/Python/Snakemake).
   

• scripts: directory contains scripts to run analyses
  
• 1_run_doubletfinder.R.ipynb: Jupyter notebook with instructions on how to run doublet detection pipeline
  
• 2_doublet_rates_per_source.R.ipynb: Jupyter notebook with instructions on how to obtain doublet rate per cluster.
  

3. 3_integration/: This directory contains Jupyter notebooks with details about how to execute code, along with scripts (R/Python/Snakemake).
   

• scripts: directory contains scripts to run analyses.
  
• 1_getMetrics.ipynb: Jupyter notebook with instructions on how to pull together multiple QC metrics. This script is different from 1_preprocessing/2_barcode_qc.ipynb as it obtains metrics from CellBender modified setting runs, while at the earlier steps, metrics come from CellBender with default settings runs.
  
• 2_integration.R.ipynb: Jupyter notebook with instructions on how to integrate data across multiple tissue sources and how to remove outlier clusters.
  
• 3_cell_annotation_final.R.ipynb: Jupyter notebook with instructions on cell annotations.

Container

A Singularity container with R and python packages for integration step can be found at https://cloud.sylabs.io/library/hhvu/r_4.3.1/r_4.3.1

Contact

Ha Vu (vthihong at umich.edu) and Stephen Parker (scjp at umich.edu)