Seurat is a mainstream tool for single-cell analysis, but its data
structure lacks a clear definition and often changes between versions.
This makes it easy to get started but difficult to master. In contrast,
SingleCellExperiment has a well-defined structure, a rich ecosystem in
R, and a corresponding Python counterpart, AnnData. Clearly, building
upon such a data structure is highly beneficial for in-depth learning
and even development. This is the motivation behind my development of
sclet—to help students in my team transition to
SingleCellExperiment.
SingleCellExperiment itself boasts a robust ecosystem, covering nearly
all types of analyses. We will also integrate existing single-cell R
packages or develop new functionalities to make them easier to use
within the SingleCellExperiment ecosystem.
Guangchuang YU
School of Basic Medical Sciences, Southern Medical University
Get the development version from github:
## install.packages("remotes")
remotes::install_github("YuLab-SMU/sclet")For more details, please refer to the online documents: