ADDS_paper

Miyoshi & Morabito et al. 2024 (Nature Genetics, in press)

This repository contains the code used for data processing and analysis in our manuscript titled "Spatial and single-nucleus trancsriptomic analysis of genetic and sporadic forms of Alzheimer's disease".

TODO: Add a brief intro

TODO:

• Clean up all notebooks
• Remove all unused code
• Provide basic comments in all scripts
• In each README section, write a short para or few sentences about the analysis.

Data generated in this study

The raw and processed ST (10X Genomics Visium) and snRNA-seq (Parse Biosciences) datasets have been deposited on the NCBI Gene Expression Omnibus (GEO) at accession number XXXXXX.

Processing sequencing data and quantifying gene expression

• Parse Biosciences snRNA-seq preprocessing scripts
• Human 10X Visium ST preprocessing scripts
• Mouse 10X Visium ST preprocessing scripts

Spatial and single-nucleus clustering analysis (Fig. 1)

snRNA-seq clustering analysis

New snRNA-seq data

• Clustering analysis for DSAD and Control data generated in this study
• Format dataset as a Seurat Object

Integration

• Integration with 3 published studies using scANVI
• Subclustering analysis of major cell lineages
• Format integrated dataset as a Seurat Object

Differential cell state analysis

• Differential cell state abundance analysis with MiloR

ST clustering analysis

Human dataset

• Load human spaceranger outputs and format as a Seurat Object
• Format human ST dataset as an anndata object, pt1
• Format human ST dataset as an anndata object, pt2
• BayesSpace clustering analysis in the human dataset

Mouse dataset

• Load mouse spaceranger outputs and format as a Seurat Object
• Format mouse ST dataset as an anndata object, pt1
• Format mouse ST dataset as an anndata object, pt2
• BayesSpace clustering analysis in the mouse dataset

Additional plotting

• Additional plotting scripts

Differential expression analysis (Figs. 2 and 4)

Note:Need to find from Emily's codebase:

• Human ST marker genes
• Human ST condition
• Mouse ST marker genes (?)

All snRNA-seq DEG scripts are there

Make a separate script for the Pseudobulk comparisons that we used for the peer review doc?

snRNA-seq differential expression

TODO: Split the Sex analysis script by snRNA vs ST ?

• Marker genes
• Disease vs Control DEG scripts
• Disease vs Control plotting and downstream analysis
• Female vs Male plotting and downstream analysis

ST differential expression

Human dataset

• Cluster marker genes
• Disease vs Control DEG scripts
• Disease vs Control plotting and downstream analysis
• Female vs Male DEG scripts
• Female vs Male plotting and downstream analysis

Mouse dataset

• Cluster marker genes
• 5xFAD vs WT DEG scripts
• 5xFAD vs WT plotting and downstream analysis
• Female vs Male DEG scripts
• Female vs Male plotting and downstream analysis

hdWGCNA co-expression network analysis (Fig. 3)

• hdWGCNA in human ST
• hdWGCNA in mouse ST

Spatial and single-nucleus genetic enrichment analysis (Fig. 3, XXX)

• Run scDRS in human snRNA datasets
• Plotting and downstream analysis of scDRS results in snRNA
• Run scDRS in human ST
• Plotting and downstream analysis of scDRS results in human ST
• Run scDRS in mouse ST
• Plotting and downstream analysis of scDRS results in mouse ST

Imaging mass cytometry (IMC) analysis (Fig. 5)

• IMC clustering analysis and downstream plotting

Predicting spatial coordinates for snRNA-seq data (Extended Data Fig. 5)

TODO: cleanup the .Rmd scripts

• Functions to run CellTrek in parallel for each snRNA-ST pair
• Running CellTrek in parallel for each snRNA-ST pair
• Downstream plotting script pt. 1
• Downstream plotting script pt. 2

Cell-cell communication (CCC) network analysis (Fig. 6)

• Cell-cell-communication network analysis with CellChat
• Cell-cell-communication network analysis with LIANA and comparing with CellChat

Amyloid-associated gene expression signatures (Fig. 7)

• Integration of amyloid imaging with ST datasets
• Human amyloid analysis
• Mouse amyloid analysis