The following guided analyses demonstrate a standard end-to-end analysis pipeline for different types of single-cell chromatin data.
In this tutorial we analyze a human peripheral blood mononuclear cell (PBMC) dataset of ~7,000 cells.
In this tutorial we analyze a dataset of ~3,500 cortical neurons from the adult mouse brain.
In this tutorial we demonstrate a joint analysis of combined gene expression and DNA accessibility data, measured in the same human PBMCs using the 10x Genomics multiomic kit.
In this tutorial we demonstrate strategies to analyze a SNARE-seq dataset where we have paired measurements of gene expression and DNA accessibility from the same mouse brain nuclei.
In this tutorial we identify clonotypes using mitochondrial DNA mutations identified from scATAC-seq data, and jointly analyze clonal cellular relationships and DNA accessibility patterns in a human colorectal cancer sample.
The following short vignettes demonstrate how to perform more specialized analysis tasks.
In this vignette we demonstrate how to perform cell-type-specific peak calling for scATAC-seq data.
This vignette outlines strategies for merging different single-cell chromatin datasets together.
Here we demonstrate the integration of multiple single-cell chromatin datasets, as well as label transfer from a reference dataset to an unlabeled query dataset.
In this vignette we demonstrate how to perform DNA sequence motif enrichment analysis using Signac.
In this vignette we demonstrate how to perform motif footprinting analysis, using a human hematopoietic stem cell dataset as an example.
Here we demonstrate how to build trajectories using scATAC-seq data with the Monocle 3 package and conversion functions present in SeuratWrappers.
Here we demonstrate how to find co-accessible peaks in scATAC-seq data using the Cicero package and conversion functions present in SeuratWrappers.
Here we demonstrate how to create genome browser-style plots using single-cell chromatin data.
The following vignettes demonstrate how to interact with the Seurat object and object classes defined in the Signac package.
This vignette details each class defined in Signac, the methods that operate on each class, and provides some examples of how to interact with these objects to perform common analysis tasks.
This vignette demonstrates how to enable parallel computing in Signac and Seurat, and gives an example of the amount of speedup that might be expected from enabling parallelization.