Pollen: Embeddings of the Pollen datasets in the principal component...
In XuegongLab/HGC: A fast hierarchical graph-based clustering method
Description
The dataset is the low dimensional principal components and
labels of cells from the Pollen dataset. The 301 cells are from
11 different cell lines and are classified into 4 tissues.
Format
An object of class list.
The list contains three elements: First, a matrix with
301 rows and 25 columns, saved as Pollen[["PCs"]]. The
rows are cells and columns are principal components. Second,
the label in tissue level, saved as a vector in
Pollen[["Tissue"]].
Third, the label in cell line level, saved as a vector in
Pollen[["CellLine"]].
Source
https://www.nature.com/articles/nbt.2967
XuegongLab/HGC documentation built on Dec. 18, 2021, 7:23 p.m.
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Description
The dataset is the low dimensional principal components and labels of cells from the Pollen dataset. The 301 cells are from 11 different cell lines and are classified into 4 tissues.
Format
An object of class list.
The list contains three elements: First, a matrix with
301 rows and 25 columns, saved as Pollen[["PCs"]]. The
rows are cells and columns are principal components. Second,
the label in tissue level, saved as a vector in
Pollen[["Tissue"]].
Third, the label in cell line level, saved as a vector in
Pollen[["CellLine"]].
Source
https://www.nature.com/articles/nbt.2967
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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