Multiome OSK

Code used to analyze the single-nuclei multiome dataset generated for the manuscript "Cognitive rejuvenation through partial reprogramming of engram cells"

• 0_multiome_objs.R: create a Seurat objects from Cell Ranger ARC outputs of different samples.
• 1_merge.R: merge all samples into a single Seurat object
• 2_QC_labelling.Rmd: RNA and ATAC QC filtering. Dimensionality reduction and clustering. Labelling of engram+ cells. Save RNA and ATAC objects.
• 3_ATAC_1_process.Rmd: ATAC data processing, dimensionality reduction and clustering.
• 3_ATAC_2_peak.R: ATAC peak calling for each annotated cell type and group using MACS2
• 3_ATAC_3_1_DA.R: Differential Accessibility Analysis.
• 3_ATAC_3_2_DA.Rmd: Differential Accessibility Analysis plotting and downstream analyses
• 3_ATAC_4_min_footprint.R: ATAC footprinting.
• 3_ATAC_5_min_motifs.Rmd: ATAC motif enrichment analysis and plotting.
• 3_ATAC_6_LinkPeaks.R: Signac Peak linking to genes in the dataset
• 3_RNA_1_composition.Rmd: cell types visualization and compositional analysis
• 3_RNA_2_DE.Rmd: Differential expression analysis
• 3_RNA_3_GSEA.Rmd: Gene Set Enrichment Analysis
• 3_RNA_3_identity.Rmd: Identity score comparison between groups
• 3_RNA_4_pseudotime.Rmd: Monocle pseudotime analysis based on engram and AD DEGs
• 3_RNA_5_CHEA3.Rmd: TF enrichment analysis of downregulated genes
• 4_integration.Rmd: Integration analyses, including RNA-ATAC correlations
• scCODA.py: compositional analysis using ths scCODA package

The sequencing data analyzed here is deposited in the Gene Expression Omnibus repository, with the series record GSE276656.

The transcriptional landscapes from Figure S7 can be visualized here.