Learn R Programming

scCustomize

scCustomize is a collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.

Vignettes/Tutorials

See accompanying scCustomize website for detailed tutorials of all aspects of scCustomize functionality.

Installing scCustomize

scCustomize can be installed from CRAN on all platforms. For more detailed instructions see Installation.

# Base R
install.packages("scCustomize")

# Using pak
pak::pkg_install("scCustomize")

Release Notes

A full copy of the changes in each version can be found in the NEWS/ChangeLog.

Develop branch
I also maintain a separate development branch* that can be installed by supplying ref = "develop" in the devtools or remotes installation command. Version scheme vX.X.X.9yyy.
*Note: While this branch is typically mostly stable it may contain breaking issues/bugs.
I do try and keep development ChangeLog up to date so it’s easier to follow changes than reading commit history.

Bug Reports/New Features

If you run into any issues or bugs please submit a GitHub issue with details of the issue.

  • If possible please include a reproducible example (suggest using SeuratData package pbmc dataset for lightweight examples.)

Any requests for new features or enhancements can also be submitted as GitHub issues.

  • Even if you don’t know how to implement/incorporate with current package go ahead a submit!

Pull Requests are welcome for bug fixes, new features, or enhancements.

  • Please set PR to merge with “develop” branch and provide description of what the PR contains (referencing existing issue(s) if appropriate).

Copy Link

Version

Install

install.packages('scCustomize')

Monthly Downloads

3,091

Version

3.0.1

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Samuel Marsh

Last Published

December 18th, 2024

Functions in scCustomize (3.0.1)

Case_Check

Check for alternate case features
Cells_per_Sample

Cells per Sample
Cell_Highlight_Plot

Meta Highlight Plot
Change_Delim_All

Change all delimiters in cell name
CellBender_Diff_Plot

Plot Number of Cells/Nuclei per Sample
Change_Delim_Prefix

Change barcode prefix delimiter
Cells.liger

Extract Cells from LIGER Object
CellBender_Feature_Diff

CellBender Feature Differences
Blank_Theme

Blank Theme
Cells_by_Identities_LIGER

Extract Cells by identity
Cluster_Highlight_Plot

Cluster Highlight Plot
Cluster_Stats_All_Samples

Calculate Cluster Stats
Copy_From_GCP

Copy folder from GCP bucket from R Console
Convert_Assay

Convert between Seurat Assay types
Extract_Modality

Extract multi-modal data into list by modality
Embeddings.liger

Extract matrix of embeddings
Copy_To_GCP

Copy folder to GCP bucket from R Console
Create_10X_H5

Create H5 from 10X Outputs
FeatureScatter_scCustom

Modified version of FeatureScatter
FeaturePlot_scCustom

Customize FeaturePlot
DimPlot_scCustom

DimPlot with modified default settings
Change_Delim_Suffix

Change barcode suffix delimiter
DimPlot_LIGER

DimPlot LIGER Version
CheckMatrix_scCustom

Check Matrix Validity
Fetch_Meta

Get meta data from object
Create_Cluster_Annotation_File

Create cluster annotation csv file
Create_CellBender_Merged_Seurat

Create Seurat Object with Cell Bender and Raw data
Find_Factor_Cor

Find Factor Correlations
ColorBlind_Pal

Color Universal Design Short Palette
Clustered_DotPlot

Clustered DotPlot
Dark2_Pal

Dark2 Palette
FeaturePlot_DualAssay

Customize FeaturePlot of two assays
Iterate_DimPlot_bySample

Iterate DimPlot By Sample
Iterate_FeaturePlot_scCustom

Iterative Plotting of Gene Lists using Custom FeaturePlots
Factor_Cor_Plot

Factor Correlation Plot
DiscretePalette_scCustomize

Discrete color palettes
Iterate_Meta_Highlight_Plot

Iterate Meta Highlight Plot
Liger_to_Seurat

Iterate_PC_Loading_Plots

Iterate PC Loading Plots
Iterate_VlnPlot_scCustom

Iterative Plotting of Gene Lists using VlnPlot_scCustom
Iterate_Cluster_Highlight_Plot

Iterate Cluster Highlight Plot
Iterate_Barcode_Rank_Plot

Iterative Barcode Rank Plots
MAD_Stats

Median Absolute Deviation Statistics
DotPlot_scCustom

Customized DotPlot
Extract_Top_Markers

Extract Top N Marker Genes
Percent_Expressing

Calculate percent of expressing cells
Extract_Sample_Meta

Extract sample level meta.data
Plot_Density_Custom

Nebulosa Density Plot
JCO_Four

Four Color Palette (JCO)
PalettePlot

Plot color palette in viewer
PC_Plotting

PC Plots
Pull_Directory_List

Pull Directory List
Plot_Density_Joint_Only

Nebulosa Joint Density Plot
QC_Histogram

QC Histogram Plots
Plot_Median_Genes

Plot Median Genes per Cell per Sample
Features.liger

Extract Features from LIGER Object
Hue_Pal

Hue_Pal
Plot_Cells_per_Sample

Plot Number of Cells/Nuclei per Sample
Feature_Present

Check if genes/features are present
DimPlot_All_Samples

DimPlot by Meta Data Column
Idents.liger

Extract or set default identities from object
QC_Plot_GenevsFeature

QC Plots Genes vs Misc
Plot_Median_Mito

Plot Median Percent Mito per Cell per Sample
QC_Plot_UMIvsFeature

QC Plots UMI vs Misc
QC_Plots_Genes

QC Plots Genes
QC_Plots_Mito

QC Plots Mito
QC_Plot_UMIvsGene

QC Plots Genes vs UMIs
Merge_Seurat_List

Merge a list of Seurat Objects
Iterate_Plot_Density_Joint

Iterative Plotting of Gene Lists using Custom Joint Density Plots
Median_Stats

Median Statistics
Pull_Cluster_Annotation

Pull cluster information from annotation csv file.
Iterate_Plot_Density_Custom

Iterative Plotting of Gene Lists using Custom Density Plots
Proportion_Plot

Cell Proportion Plot
Meta_Numeric

Check if meta data columns are numeric
Meta_Highlight_Plot

Meta Highlight Plot
Meta_Present

Check if meta data are present
QC_Plots_Complexity

QC Plots Cell "Complexity"
Read_GEO_Delim

Load in NCBI GEO data formatted as single file per sample
Read_CellBender_h5_Multi_File

Load CellBender h5 matrices (corrected) from multiple files
Meta_Remove_Seurat

Remove meta data columns containing Seurat Defaults
Read10X_GEO

Load in NCBI GEO data from 10X
Plot_Median_Other

Plot Median other variable per Cell per Sample
Plot_Median_UMIs

Plot Median UMIs per Cell per Sample
Read10X_h5_GEO

Load in NCBI GEO data from 10X in HDF5 file format
Read10X_h5_Multi_Directory

Load 10X h5 count matrices from multiple directories
Seq_QC_Plot_Genes

QC Plots Sequencing metrics
Seq_QC_Plot_Exonic

QC Plots Sequencing metrics (Alignment)
Read_CellBender_h5_Mat

Load CellBender h5 matrices (corrected)
Read10X_Multi_Directory

Load 10X count matrices from multiple directories
Seq_QC_Plot_Intronic

QC Plots Sequencing metrics (Alignment)
Seq_QC_Plot_Number_Cells

QC Plots Sequencing metrics
Seq_QC_Plot_Saturation

QC Plots Sequencing metrics
Seq_QC_Plot_Antisense

QC Plots Sequencing metrics (Alignment)
QC_Plots_Feature

QC Plots Feature
Seq_QC_Plot_Basic_Combined

QC Plots Sequencing metrics (Layout)
Split_Vector

Split vector into list
Seq_QC_Plot_Reads_in_Cells

QC Plots Sequencing metrics
Seq_QC_Plot_Reads_per_Cell

QC Plots Sequencing metrics
Stacked_VlnPlot

Stacked Violin Plot
Merge_Sparse_Multimodal_All

Merge a list of Sparse Matrices contain multi-modal data.
NavyAndOrange

Navy and Orange Dual Color Palette
Merge_Sparse_Data_All

Merge a list of Sparse Matrices
Move_Legend

Move Legend Position
Random_Cells_Downsample

Randomly downsample by identity
UnRotate_X

Unrotate x axis on VlnPlot
QC_Plots_UMIs

QC Plots UMIs
Updated_HGNC_Symbols

Update HGNC Gene Symbols
Variable_Features_ALL_LIGER

Perform variable gene selection over whole dataset
Split_FeatureScatter

Seq_QC_Plot_Total_Genes

QC Plots Sequencing metrics
Seq_QC_Plot_Genome

QC Plots Sequencing metrics (Alignment)
Read_Metrics_10X

Read Overall Statistics from 10X Cell Ranger Count
Seq_QC_Plot_Intergenic

QC Plots Sequencing metrics (Alignment)
Read_Metrics_CellBender

Read Overall Statistics from CellBender
ensembl_hemo_id

Ensembl Hemo IDs
Reduction_Loading_Present

Check if reduction loadings are present
QC_Plots_Combined_Vln

QC Plots Genes, UMIs, & % Mito
VlnPlot_scCustom

VlnPlot with modified default settings
Single_Color_Palette

Single Color Palettes for Plotting
WhichCells.liger

Extract Cells for particular identity
Setup_scRNAseq_Project

Setup project directory structure
Store_Palette_Seurat

Store color palette in Seurat object
Store_Misc_Info_Seurat

Store misc data in Seurat object
theme_ggprism_mod

Modified ggprism theme
seq_zeros

Create sequence with zeros
Seq_QC_Plot_Transcriptome

QC Plots Sequencing metrics (Alignment)
Read_CellBender_h5_Multi_Directory

Load CellBender h5 matrices (corrected) from multiple directories
scCustomize-package

scCustomize: Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
as.LIGER

Convert objects to LIGER objects
viridis_plasma_dark_high

Viridis Shortcuts
msigdb_qc_gene_list

QC Gene Lists
msigdb_qc_ensembl_list

QC Gene Lists
ensembl_ribo_id

Ensembl Ribo IDs
ieg_gene_list

Immediate Early Gene (IEG) gene lists
Seq_QC_Plot_UMIs

QC Plots Sequencing metrics
VariableFeaturePlot_scCustom

Custom Labeled Variable Features Plot
as.Seurat.liger

Convert objects to Seurat objects
Split_Layers

Split Seurat object into layers
Replace_Suffix

Replace barcode suffixes
SpatialDimPlot_scCustom

SpatialDimPlot with modified default settings
scCustomize_Palette

Color Palette Selection for scCustomize
as.anndata

Convert objects to anndata objects
Updated_MGI_Symbols

Update MGI Gene Symbols
Top_Genes_Factor

Extract top loading genes for LIGER factor
Rename_Clusters

Rename Clusters
Seq_QC_Plot_Alignment_Combined

QC Plots Sequencing metrics (Alignment) (Layout)
plotFactors_scCustom

Customized version of plotFactors
ensembl_mito_id

Ensembl Mito IDs
Subset_LIGER

Subset LIGER object
ensembl_ieg_list

Immediate Early Gene (IEG) gene lists
reexports

Objects exported from other packages
Add_Top_Gene_Pct

Add Percent of High Abundance Genes
Barcode_Plot

Create Barcode Rank Plot
Add_Cell_QC_Metrics

Add Multiple Cell Quality Control Values with Single Function
Add_Sample_Meta

Add Sample Level Meta Data
Add_Mito_Ribo

Add Mito and Ribo percentages
Add_Alt_Feature_ID

Add Alternative Feature IDs
Add_Hemo

Add Hemoglobin percentages
Add_CellBender_Diff

Calculate and add differences post-cell bender analysis
Add_Pct_Diff

Add percentage difference to DE results
Add_Cell_Complexity

Add Cell Complexity