The datacleaning package offers a suite of functions designed to enhance the process of cleaning up and visualizing clusters within a Seurat object, commonly used for single-cell RNA sequencing (scRNA-seq) data analysis. It includes functions for cropping clusters, reassigning cells to new clusters based on UMAP coordinates, visualizing the refined clusters, updating cell identities based on specified clusters and visualizing the resulting data using UMAP plots.
To install the package from GitHub, utilize the devtools package:
devtools::install_github("fmbetul/datacleaning")To use the package, load it into your R session:
library(datacleaning)Below is an example showcasing the use of various functions within this package:
# Assuming `SeuratObject` is your Seurat object
# Step 1: Apply CropCluster() to each cluster needing cropping, either by providing ClusterNo or ClusterName
cropCluster(SeuratObject, ClusterName = "Cluster1", min.x = -10, max.y = 10)
cropCluster(SeuratObject, ClusterName = "Cluster2", min.x = -5, min.y = 5)# Step 2: Assign leftover cells to a new cluster, set validate = TRUE after you feel satisfied with the new cluster.
assignNewCluster(SeuratObject, ClusterName = "Cluster3", min.x = -10, max.y = 10, validate = TRUE)
assignNewCluster(SeuratObject, ClusterName = "Cluster4", min.x = -5, min.y = -5, validate = TRUE)# Step 3: Obtain the final cleaned-up clusters
SeuratObject <- getFinalClusters(SeuratObject)For more information on available functions and their usage, please refer to the package documentation.
The datacleaning package has the following dependencies:
- R (>= 3.6.0)
- Seurat (>= 4.0.0)
This package is licensed under the GNU General Public License version 3 (GPL-3). See the LICENSE file for more details.
If you encounter any issues with the datacleaning package or would like to contribute to its development, please open an issue on GitHub.
For any further inquiries or questions, please feel free to contact the package maintainer, F. M. Betul Erol, at [email protected].