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1
Getting Started with ArchR
1.1
A Brief Primer on ATAC-seq Terminology
1.2
Why use ArchR?
1.3
What is an Arrow file /
ArchRProject
?
1.4
Input File Types in ArchR
1.5
Getting Set Up
1.6
Creating Arrow Files
1.7
Per-cell Quality Control
2
Doublet Inference with ArchR
2.1
How does doublet identification work in ArchR?
2.2
Inferring scATAC-seq Doublets with ArchR
3
Creating an ArchRProject
3.1
Creating An ArchRProject
3.2
Manipulating An ArchRProject
3.3
Plotting Sample Statistics from an ArchRProject
3.4
Plotting Sample Fragment Size Distribution and TSS Enrichment Profiles.
3.5
Saving and Loading an
ArchRProject
3.6
Filtering Doublets from an ArchRProject
4
Dimensionality Reduction with ArchR
4.1
ArchR’s LSI Implementation
4.2
Iterative Latent Semantic Indexing (LSI)
4.3
Estimated LSI
4.4
Batch Effect Correction wtih Harmony
5
Clustering with ArchR
5.1
Clustering using Seurat’s
FindClusters()
function
6
Single-cell Embeddings
6.1
Uniform Manifold Approximation and Projection (UMAP)
6.2
t-Stocastic Neighbor Embedding (t-SNE)
6.3
Dimensionality Reduction After Harmony
7
Gene Scores and Marker Genes with ArchR
7.1
Calculating Gene Scores in ArchR
7.2
Identification of Marker Features
7.3
Identifying Marker Genes
7.4
Visualizing Marker Genes on an Embedding
7.5
Marker Genes Imputation with MAGIC
7.6
Track Plotting with ArchRBrowser
7.7
Launching the ArchRBrowser
8
Defining Cluster Identity with scRNA-seq
8.1
Cross-platform linkage of scATAC-seq cells with scRNA-seq cells
8.2
Adding Pseudo-scRNA-seq profiles for each scATAC-seq cell
8.3
Labeling scATAC-seq clusters with scRNA-seq information
9
Pseudo-bulk Replicates in ArchR
9.1
How Does ArchR Make Pseudo-bulk Replicates?
9.2
Making Pseudo-bulk Replicates
10
Calling Peaks with ArchR
10.1
The Iterative Overlap Peak Merging Procedure
10.2
Calling Peaks w/ Macs2
10.3
Calling Peaks w/ TileMatrix
10.4
Add Peak Matrix
11
Identifying Marker Peaks with ArchR
11.1
Identifying Marker Peaks with ArchR
11.2
Plotting Marker Peaks in ArchR
11.3
Pairwise Testing Between Groups
12
Motif and Feature Enrichment with ArchR
12.1
Motif Enrichment in Differential Peaks
12.2
Motif Enrichment in Marker Peaks
12.3
ArchR Enrichment
12.4
Custom Enrichment
13
ChromVAR Deviatons Enrichment with ArchR
13.1
Motif Deviations
13.2
ArchR and Custom Deviations
14
Footprinting with ArchR
14.1
Motif Footprinting
14.2
Normalization of Footprints for Tn5 Bias
14.3
Feature Footprinting
15
Integrative Analysis with ArchR
15.1
Creating Low-Overlapping Aggregates of Cells
15.2
Co-accessibility with ArchR
15.3
Peak2GeneLinkage with ArchR
15.4
Identification of Positive TF-Regulators
16
Trajectory Analysis with ArchR
16.1
Myeloid Trajectory - Monocyte Differentiation
16.2
Lymphoid Trajectory - B Cell Cifferentiation
17
Plot aesthetics in ArchR
18
Session Information
Published with bookdown
ArchR: Robust and scaleable analysis of single-cell chromatin accessibility data.
Chapter 17
Plot aesthetics in ArchR
Coming soon…