SinCellTE 2022 Single-cell Epigenomics & Multi-omics integration

Welcome to the SinCellTE 2022 Single-cell Epigenomics & Multi-omics integration tutorial This tutorial is divided in two sessions:

On the first session we will guide you through all the necessary steps to perform a complete analysis of single-cell chromatin accessiblity (scATAC-seq) data, from raw files to inferring enrichment of transcription factors.
On the second session we will focus on different strategies to combine scATAC-seq data with scRNA-seq data, from assays where both modalities were measured from the same cell.

Tutors

Carl Herrmann, Health Data Science Unit Medical Faculty Heidelberg and BioQuant (carl.herrmann@bioquant.uni-heidelberg.de)
Andres Quintero, Health Data Science Unit Medical Faculty Heidelberg and BioQuant (andres.quintero@bioquant.uni-heidelberg.de)

Schedule

Activity	Time
Session 1 - scATAC-seq analysis
Introduction to single-cell epigenomics	9:00 - 10:15
Hands-on: Analysis of scATAC-seq data	10:45 - 12:30
Lunch break	13:00 - 14:15
Session 2 - Multi-omics integration
Introduction to multi-mics analysis	14:30 - 15:15
Hands-on: Integrative analysis of scATAC-seq/scRNA-seq data	15:15 - 16:00

Practical sessions

Please document your progress in this Google Sheet

Session 1 - scATAC-seq analysis

On the "scATAC-seq analysis" session we will focus on understanding the basic steps to perform a scATAC-seq data analysis. We wil use two of the most frequently used packages: ArchR and Signac. Additonally we will see a few tips to format the raw data in order to be used by these packages.

Session 2 - Multi-omics integration

On the "Multi-omics integration" session we will complete an integrative analysis of single-cell chromatin accessibility and transcriptome data, using ArchR and Signac.