Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
Add Alternative Feature IDs
Add Cell Complexity
Add Multiple Cell Quality Control Values with Single Function
Calculate and add differences post-cell bender analysis
Add Hemoglobin percentages
Add Mito and Ribo percentages
Add percentage difference to DE results
Add Sample Level Meta Data
Add Percent of High Abundance Genes
Convert objects to anndata objects
Convert objects to LIGER objects
Convert objects to Seurat
objects
Create Barcode Rank Plot
Blank Theme
Check for alternate case features
Meta Highlight Plot
Plot Number of Cells/Nuclei per Sample
CellBender Feature Differences
Extract Cells by identity
Cells per Sample
Extract Cells from LIGER Object
Change all delimiters in cell name
Change barcode prefix delimiter
Change barcode suffix delimiter
Check Matrix Validity
Cluster Highlight Plot
Calculate Cluster Stats
Clustered DotPlot
Color Universal Design Short Palette
Convert between Seurat Assay types
Copy folder from GCP bucket from R Console
Copy folder to GCP bucket from R Console
Create H5 from 10X Outputs
Create Seurat Object with Cell Bender and Raw data
Create cluster annotation csv file
Dark2 Palette
Deprecated functions
DimPlot by Meta Data Column
DimPlot LIGER Version
DimPlot with modified default settings
Discrete color palettes
Customized DotPlot
Extract matrix of embeddings
Extract multi-modal data into list by modality
Extract sample level meta.data
Extract Top N Marker Genes
Factor Correlation Plot
Check if genes/features are present
Customize FeaturePlot of two assays
Customize FeaturePlot
Extract Features from LIGER Object
Modified version of FeatureScatter
Get meta data from object
Find Factor Correlations
Hue_Pal
Extract or set default identities from object
Iterative Barcode Rank Plots
Iterate Cluster Highlight Plot
Iterate DimPlot By Sample
Iterative Plotting of Gene Lists using Custom FeaturePlots
Iterate Meta Highlight Plot
Iterate PC Loading Plots
Iterative Plotting of Gene Lists using Custom Density Plots
Iterative Plotting of Gene Lists using Custom Joint Density Plots
Iterative Plotting of Gene Lists using VlnPlot_scCustom
Four Color Palette (JCO)
Create a Seurat object containing the data from a liger object
Median Absolute Deviation Statistics
Median Statistics
Merge a list of Seurat Objects
Merge a list of Sparse Matrices
Merge a list of Sparse Matrices contain multi-modal data.
Meta Highlight Plot
Check if meta data columns are numeric
Check if meta data are present
Remove meta data columns containing Seurat Defaults
Move Legend Position
Navy and Orange Dual Color Palette
Plot color palette in viewer
PC Plots
Calculate percent of expressing cells
Plot Number of Cells/Nuclei per Sample
Nebulosa Density Plot
Nebulosa Joint Density Plot
Plot Median Genes per Cell per Sample
Plot Median Percent Mito per Cell per Sample
Plot Median other variable per Cell per Sample
Plot Median UMIs per Cell per Sample
Customized version of plotFactors
Cell Proportion Plot
Pull cluster information from annotation csv file.
Pull Directory List
QC Histogram Plots
QC Plots Genes vs Misc
QC Plots UMI vs Misc
QC Plots Genes vs UMIs
QC Plots Genes, UMIs, & % Mito
QC Plots Cell "Complexity"
QC Plots Feature
QC Plots Genes
QC Plots Mito
QC Plots UMIs
Randomly downsample by identity
Load CellBender h5 matrices (corrected)
Load CellBender h5 matrices (corrected) from multiple directories
Load CellBender h5 matrices (corrected) from multiple files
Load in NCBI GEO data formatted as single file per sample
Read Overall Statistics from 10X Cell Ranger Count
Read Overall Statistics from CellBender
Load in NCBI GEO data from 10X
Load in NCBI GEO data from 10X in HDF5 file format
Load 10X h5 count matrices from multiple directories
Load 10X count matrices from multiple directories
Check if reduction loadings are present
Objects exported from other packages
Rename Clusters
Replace barcode suffixes
Color Palette Selection for scCustomize
scCustomize: Custom Visualizations & Functions for Streamlined Analyse...
QC Plots Sequencing metrics (Alignment) (Layout)
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics (Layout)
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics
QC Plots Sequencing metrics
QC Plots Sequencing metrics
QC Plots Sequencing metrics
QC Plots Sequencing metrics
QC Plots Sequencing metrics (Alignment)
QC Plots Sequencing metrics
Create sequence with zeros
Setup project directory structure
Single Color Palettes for Plotting
SpatialDimPlot with modified default settings
Split Seurat object into layers
Split vector into list
Stacked Violin Plot
Store misc data in Seurat object
Store color palette in Seurat object
Subset LIGER object
Modified ggprism theme
Extract top loading genes for LIGER factor
Unrotate x axis on VlnPlot
Update HGNC Gene Symbols
Update MGI Gene Symbols
Perform variable gene selection over whole dataset
Custom Labeled Variable Features Plot
Viridis Shortcuts
VlnPlot with modified default settings
Extract Cells for particular identity
Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.
Useful links