Analyzing PBMCs Single Cell ATAC- Seq (scATAC-Seq) and Multiome data: Theory and practice

Author

Evelia Coss and Diego Ramirez

Published

October 17, 2024

Global information

  • This course is part of the Workshop Single Cell Genomic Approaches to Study the Immune System - Latin America & the Caribbean (9-11 Novembrer 2024), Universidad CES, MedellΓ­n, Colombia.

    • Date: 11 November 2024

    • Course duration: 5 hours

    Course Instructors:

    • Diego Ramirez - Bachelor in Genomic Sciences, Escuela Nacional de Estudios Superiores Unidad Juriquilla UNAM (ENES Juriquilla), Mexico.

    • Evelia Lorena Coss-Navarrete - PostDoc, International Laboratory for Human Genome Research (LIIGH)-UNAM, Mexico. Contact: Web page

    Abstract:

    Single-cell transposase-accessible chromatin sequencing (scATAC-seq) represents the most innovative technology for examining genome-wide regulatory landscapes in single cells. For this tutorial, we will be analyzing a single-cell ATAC-seq dataset of human peripheral blood mononuclear cells (PBMCs) provided by 10x Genomics. We will run bridge integration for PBMC with the newly released Azimuth ATAC workflow. In this workshop we will review the existing statistical tools for analyzing scATAC-seq data, how to document your analysis and review some tools for interpreting results.

    Learning objectives:

    1. Fundamentals of Single Cell ATAC-seq (scATAC-seq) and Multiome analysis.

    2. Single-Cell ATAC-seq Pre-Processing and Quality Control.

    3. Loading in and pre-processing the scATAC-seq, multiome, and scRNA-seq reference datasets.

    4. Mapping the scATAC-seq dataset via bridge integration.

    5. Exploring and assessing the resulting annotations.

    6. Motif analysis with Signac

    Citing and Re-using Course Material

    The course data are free to reuse and adapt with appropriate attribution. All course data in these repositories are licensed under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

    Subject Time Instructor
    πŸ”· Section 1 - Introduction and Quality control (45 min) - (9:45-10:30 h)
    • Fundamentals of Single Cell ATAC-seq (scATAC-seq) analysis
    15 min (9:45- 10:00) Evelia Coss
    • Practical 13: scATAC-seq Pre-Processing and Quality Control
    30 min
    (10:00-10:30)
    Evelia Coss
    β˜• Coffee break (30 min) - (10:30-11:00 h) β˜•
    πŸ”· Section 2 - scATAC-seq Downstream analysis (2 h) - (11:00-13:00 h)
    • Practical 14: scATAC-seq Downstream
    1 h
    (11:00-12:00)
    Diego Ramirez
    • Practical 15: Analyses and scRNA-seq Integration
    1 h
    (12:00-13:00)
    Diego Ramirez
    πŸ–πŸ— Lunch (1 h) - (13:00 - 14:00) πŸ–πŸ—
    πŸ”· Section 3 - Motif analysis and results (14:00 - 15:30 h)
    • Practical 16: Motif analysis with Signac
    30 min
    (14:00-14:30)
    Diego Ramirez
    • Practical 17: Exploring results (graphs)
    30 min (14:30-15:00) Diego Ramirez
    • Other tools used in scATAC-seq
    30 min (15:00-15:30) Evelia Coss and Diego Ramirez

    πŸ”· Section 1 - Practical 13

    For this tutorial, we will be analyzing a single-cell ATAC-seq dataset of human peripheral blood mononuclear cells (PBMCs) provided by 10x Genomics (Next GEM v1.1). The following files are used in this course, all available through the 10x Genomics website:

    Google Colab - Practical 13

    πŸ”· Section 2 - Practical 14

    For this tutorial, we will use the results from Practical 13, where we analyzed a single-cell ATAC-seq dataset of human peripheral blood mononuclear cells (PBMCs). Additionally, we will use the pre-processed Seurat object available here.

    • Download the file previously generated in the previous practice (Practical 13). If you did not download it (β€œpbmc.RData”) then download it by clicking here and upload the file to google colab.

    Google Colab - Practical 14

    πŸ”· Section 2 - Practical 15

    For this tutorial, we will be analyzing a single-cell ATAC-seq dataset of human peripheral blood mononuclear cells (PBMCs) (3K) provided by 10x Genomics (Cell Ranger ARC 2.0.0). The following files are used in this course, all available through the 10x Genomics website:

    Google Colab - Practical 15

    πŸ”· Section 3 - Practical 16

    For this tutorial, we will be analyzing a single-cell ATAC-seq dataset of human peripheral blood mononuclear cells (PBMCs) provided by 10x Genomics (Next GEM v1.1). The following files are used in this course, all available through the 10x Genomics website:

    Google Colab - Practical 16

    • From CRAN:

      • Seurat, cowplot, SingleCellExperiment, scDblFinder, Rtsne, hdf5r, clustree, tidyverse, Signac, SeuratObject, hdf5r, reticulate, patchwork, ggplot2, future.
    • From Bioconductor:

      • celldex, SingleR, SeuratDisk, clusterProfile, preprocessCore, EnsDb.Hsapiens.v86, EnsDb.Hsapiens.v75, biovizBase, LoomExperiment, SingleCellExperiment, SeuratData, JASPAR2020, TFBSTools, glmGamPoi, clusterProfiler, org.Hs.eg.db , BSgenome.Hsapiens.UCSC.hg38
    • From Github:

      • SeuratData, presto and sceasy