Preface
1
Basic: preprocessing and clustering
1.1
Read 10X data
1.2
QC
1.3
Variable features
1.4
Dimensional reduction
1.5
Clustering
1.6
UMAP
1.7
Find Markers
1.7.1
Marker gene information
1.8
Cell cluster annotation
2
Cell type annotation
2.1
Manual annotation
2.2
Automatic annotation
2.2.1
Run SingleR
2.2.2
Annotate with SingleR result
2.2.3
Comparision with manual annotation result
3
Cell-cell communication
3.1
Input
3.2
CellChat
3.3
visulization
4
SVP
4.1
runSGSA
4.2
runLISA
4.3
runLOCALBV
sclet: A Lightweight Toolkit for Single-Cell Data Analysis
sclet: A Lightweight Toolkit for Single-Cell Data Analysis
Guangchuang Yu
Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University
guangchuangyu@gmail.com
2024-10-09
Preface
Hello World.