Front matter
Abstract
Declaration
Preface
Acknowledgements
List of copyright
1
Introduction
1.1
The central dogma
1.2
RNA sequencing
1.2.1
Library preparation
1.2.2
High-throughput sequencing
1.2.3
Analysis of RNA-seq data
1.3
Single-cell RNA sequencing
1.3.1
Early single-cell capture technologies
1.3.2
Droplet-based cell capture
1.3.3
Unique Molecular Identifiers
1.3.4
Recent advances in scRNA-seq protocols
1.4
Analysing scRNA-seq data
1.4.1
Pre-processing and quality control
1.4.2
Normalisation and integration
1.4.3
Grouping cells
1.4.4
Ordering cells
1.4.5
Gene detection and interpretation
1.4.6
Alternative analyses
1.4.7
Evaluation of scRNA-seq analysis methods
1.5
Kidney development
1.5.1
Structure and function
1.5.2
Stages of development
1.5.3
Growing kidney organoids
1.5.4
Kidney scRNA-seq studies
1.6
Thesis overview and aims
2
The scRNA-seq tools landscape
2.1
Introduction
2.2
scRNA-tools publication
2.3
The current scRNA-tools database
2.4
Usage of the scRNA-tools website
3
Simulating scRNA-seq data
3.1
Introduction
3.2
Splatter publication
3.3
Updates to Splatter
3.3.1
Performance of current simulations
4
Visualising clustering across resolutions
4.1
Introduction
4.2
Clustering trees publication
4.3
Overlaying clustering trees
5
Analysis of kidney organoid scRNA-seq data
5.1
Introduction
5.2
Summary of published work
5.3
Outline and motivation
5.4
Pre-processing
5.4.1
Droplet selection
5.4.2
Alevin comparison
5.5
Quality control
5.6
Clustering
5.6.1
Gene selection
5.6.2
Resolution selection
5.6.3
Cluster validation
5.6.4
Comparison to published clusters
5.7
Marker gene detection
5.8
Connecting clusters
5.8.1
Partition-based graph abstraction
5.8.2
Cell velocity
5.9
Discussion
6
Conclusion
References
Appendix
A
Splatter additional files
A.1
Additional figures
A.2
Session information
B
Splatter documentation
B.1
Splatter vignette
B.2
Splat parameters vignette
B.3
Splatter manual
C
Simulation comparison
C.1
Timings
C.2
Package versions
D
clustree documentation
D.1
clustree vignette
D.2
clustree manual
E
Kidney organoid publication
F
Analysis methods
F.1
Pre-processing
F.1.1
Droplet selection
F.1.2
Alevin
F.2
Quality control
F.3
Clustering
F.3.1
Gene selection
F.3.2
Graph-based clustering
F.4
Marker genes
F.5
Partition-based graph abstraction (PAGA)
F.6
Cell velocity
F.7
Other packages
G
Session information
G.1
Important packages
G.2
Full session information
Published with bookdown
Tools and techniques for single-cell RNA sequencing data
D
clustree documentation
D.1
clustree vignette
You can read the clustree vignette
here
.
D.2
clustree manual
You can read the clustree manual
here
.