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scATAC-seq PBMC Analysis

Complete Signac Workflow for Chromatin Accessibility Analysis

Ravi Shanker Pandey, Ph.D. Associate Computational Scientist | The Jackson Laboratory


Overview

Complete scATAC-seq analysis of 10x Genomics PBMC data using Signac — from raw fragment files through QC, dimensionality reduction, clustering, gene activity scoring, and cell type annotation.


Key Findings

  • 4,560 high-quality cells after QC filtering
  • 11 clusters → 6 immune cell types identified
  • LSI_1 excluded (correlated with sequencing depth)
  • Cell types: CD4 T, CD8 T, NK, B cells, Monocytes, Dendritic cells

Methods

Fragment file → Peak matrix → QC filtering → TF-IDF normalization → LSI/SVD → DepthCor (exclude LSI_1) → UMAP → Leiden clustering → Gene activity scores → Cell type annotation

QC Metrics

Metric Cutoff Result
% Reads in peaks >15% Median 75% ✅
Blacklist ratio <0.05 ~0.000 ✅
Nucleosome signal <4 Median 0.57 ✅
TSS enrichment >2 Median 6.19 ✅

Requirements

library(Signac)      # >= 1.17
library(Seurat)      # >= 5.0
library(EnsDb.Hsapiens.v86)
library(biovizBase)

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Complete scATAC-seq analysis of PBMC data using Signac — QC, TF-IDF normalization, LSI dimensionality reduction, clustering, gene activity scoring and cell type annotation

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