PirbrightBAL-muir

This repository contains analysis markdown files and scripts for analysing porcine BAL scRNAseq data as a collaborative work between the Babraham institute and Pirbright Institute. Results are now published in PLOS Pathogens, titled; 'Single-cell analysis reveals lasting immunological consequences of influenza infection and respiratory immunisation in the pig lung'.

Original unprocessed data can be downloaded from GEO(GSE249866). https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE249866

To replicate the analysis performed in the published paper, download the fastq.gz files from GEO(GSE249866) and perform alignment/counting using cellranger count (cellranger-7.0.0) using default parameters and Sus scrofa genome (genome assembly 11.1, Ensembl release 107) to regenerate files used in the original analysis. Example cellranger commands can be found in '/cluster scripts'.

Directory should look like this for each sample folder:

• sample1 folder
  • molecule_info.h5
  • raw_feature_bc_matrix.h5 also available on GEO
  • filtered_feature_bc_matrix.h5 also available on GEO
  • raw_feature_bc_matrix folder
    • barcodes.tsv.gz
    • features.tsv.gz
    • matrix.mtx.gz
  • filtered_feature_bc_matrix folder
    • barcodes.tsv.gz
    • features.tsv.gz
    • matrix.mtx.gz

Scripts in this directory are run in the following order:

1. processing_all.Rmd Reads in cellranger output (see above) and performs initial filtering and QC.
2. clustering_all.Rmd Clustering and cluster inspection.
3. differential_all.Rmd Cell type annotation followed by an initial differential expression analysis utilising a pseudobulk approach.

The following scripts can be run in any order, provided the scripts above have been run.

• Validation_vs_PBMC.Rmd Comparative analysis between the clusters and cell types identified in the pig BAL against the reference PBMC transcriptome published by Herrera-Uribe et al. 2021 (https://doi.org/10.3389%2Ffgene.2021.689406).
• diff-co_NEBULA.Rmd Differential expression and co-expression analysis with NEBULA as well as topGO enrichment of the identified genes.
• Treg_pseudobulk_volcanoes.Rmd Short script to generate volcano plots of differentially expressed genes from Tregs derived from the pseudobulk analysis in differential_all.Rmd. This script was used for responding to reviewers comments and doesn't generate data for the related paper.
• diff-co.Rmd Initial look at differential co-expression using dcanr. Not utilised in paper.

shiny_app/data.rds to use for data exploration in the shiny app shiny_app/app.R is generated by clustering all.Rmd (unannotated data) and differential_all.Rmd (annotated and normalised data).