Skip to main content
Ctrl+K

SnapATAC2

  • Installation
  • Tutorials
  • API reference
  • Development
  • Release notes
  • Learn
  • GitHub
  • Installation
  • Tutorials
  • API reference
  • Development
  • Release notes
  • Learn
  • GitHub

Section Navigation

  • Standard pipeline: analyzing 5K PBMC dataset from 10X genomics
  • Annotating cell clusters by integrating single-cell RNA-seq data
  • Identify differentially accessible regions
  • Multi-sample Pipeline: analyzing snATAC-seq data of human colon samples
  • Multi-modality pipeline: analyzing single-cell multiome data (ATAC + Gene Expression)
  • Atlas-scale Analysis: a cell atlas of human chromatin accessibility.
  • Tutorials

Tutorials#

  • Standard pipeline: analyzing 5K PBMC dataset from 10X genomics
    • Introduction
    • Import library and environment setup
    • Preprocessing
    • Dimension reduction
    • Clustering analysis
    • Cell cluster annotation
    • What’s next?
  • Annotating cell clusters by integrating single-cell RNA-seq data
    • Introduction
    • Preparing data
    • Data integration
    • What’s next?
  • Identify differentially accessible regions
    • Peak calling at the cluster-level
    • Finding marker regions
    • Regression-based differential test
  • Multi-sample Pipeline: analyzing snATAC-seq data of human colon samples
    • Introduction
    • Creating AnnDataSet object
    • Batch correction
    • Clustering
    • Peak calling
    • AnnDataSet object IO
  • Multi-modality pipeline: analyzing single-cell multiome data (ATAC + Gene Expression)
    • Introduction
    • Analyze gene expression data
    • Analyze chromatin accessibility data
    • Perform joint embedding
  • Atlas-scale Analysis: a cell atlas of human chromatin accessibility.
    • Introduction
    • Preprocessing
    • Dimensionality reduction
    • Batch correction
    • Clustering
    • Visualization
    • Subclustering

previous

Installation

next

Standard pipeline: analyzing 5K PBMC dataset from 10X genomics

© Copyright 2022-2024, Kai Zhang.

Built with the PyData Sphinx Theme 0.16.0.