SingleCell Workshop 2021
1
Introduction
1.1
Contents of this part
1.2
Other modules of this workshop
2
Prerequisites
2.1
R packages
2.2
Python packages
2.2.1
Installation on Windows
2.2.2
Installation on macOS
2.2.3
Installation on Linux
3
Trajectory inference and RNA velocity
3.1
Trajectory inference
3.1.1
Diffusion map
3.1.2
Monocle
3.2
RNA velocity
3.2.1
RNA kinetics
3.2.2
Unspliced RNA indicates transcriptional speed
3.3
scVelo in R
3.3.1
Getting started
3.3.2
Data Preprocessing
3.3.3
Diffusion pseudotime
3.3.4
Compute velocity and velocity graph
3.3.5
Diffusion pseudotime with velocity
3.3.6
Visualise velocity-based trajectory
3.3.7
Interprete Velocity
3.3.8
Velocity in cycling progenitors
3.3.9
Dynamical Mode and related analysis
3.4
Last notes
4
Somatic mutation analysis in single cells
4.1
Introduction
4.1.1
Choice of protocols
4.2
SNV analysis
4.2.1
Call somatic variants and genotype single cells
4.2.2
Visualize variat allele fequency
4.2.3
Use extra information on clonal tree
4.2.4
Run cardelino for inferring clonal structure
4.3
mtSNV analysis
4.3.1
Visualise allele frequency
4.3.2
Infer clonal structure with mtDNA variants
4.4
Last notes
5
Copy number variation estimation from scRNA-seq
5.1
Introduction
5.2
inferCNV and example
5.2.1
install inferCNV
5.2.2
getting started
5.3
Application on TNBC1
5.3.1
data description
5.3.2
run inferCNV
5.3.3
inferCNV result
5.4
Last notes
6
Preprocessing of dataset
6.1
Preprocessing for RNA Velocity
6.1.1
List of packages aligned in pipeline:
6.1.2
Installation of packages/softwares
6.1.3
Preprocessing pipline
6.2
Preprocessing for somatic mutation analysis
6.2.1
Pileup with cellsnp-lite
6.2.2
Clonal analysis with MQuad
6.3
(Optional) Install Windows Subsystem for Linux
6.3.1
What is the Windows Subsystem for Linux (WSL)?
6.3.2
Manual Installation Steps
References
Published with bookdown
HKU Single-cell Workshop (Modules 4.2 & 5)
References