R: Geometric Single Cell Deconvolution

# Geometric Single Cell Deconvolution

## Documentation for package ‘cellGeometry’ version 0.6.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_noise | Add noise to count data
adjust_library_size | Adjust count matrix by library size
cellMarkers | Identify cell markers
collapse_group | Collapse groups in cellMarkers object
comp_heatmap | Compensation heatmap
confint.deconv | Confidence Intervals for Deconvolution Models
cooks.distance.deconv | Regression Deletion Diagnostics
cos_similarity | Gene signature cosine similarity matrix
deconvolute | Deconvolute bulk RNA-Seq using single-cell RNA-Seq signature
diagnose | Diagnostics for cellMarker signatures
fix_bulk | Fix in missing genes in bulk RNA-Seq matrix
fix_group | Fix cellMarkers signature with no cell groups
gene2symbol | Converts ensembl gene ids to symbols
generate_samples | Generate random cell number samples
gene_angle | Vector based best marker selection
ggplot_residuals | Residuals plot
graded_log_noise | Add noise to count data
kappa.deconv | Compute condition number of deconvolution model
log2s | Mean Objects
logmean | Mean Objects
log_noise | Add noise to count data
max_similarity | Maximum similarity between cell types
mergeMarkers | Merge cellMarker signatures
metric_set | Calculate R-squared and metrics on deconvoluted cell subclasses
plot.qqmap | Quantile-quantile plot
plot_biasvar | Plot bias-variance decomposition
plot_comp | Plot compensation analysis
plot_cv | Plot deconvolution lambda cross-validation curve
plot_path | Plot compensation analysis
plot_pred | Scatter plot to compare deconvoluted subclasses
plot_residuals | Residuals plot
plot_set | Scatter plots to compare deconvoluted subclasses
plot_tune | Plot tuning curves
quantile_map | Quantile mapping function between two scRNA-Seq datasets
rank_angle | Rank distance angles from a cosine similarity matrix
reduceNoise | Reduce noise in single-cell data
residuals.deconv | Extract Deconvolution Residuals
rstandard.deconv | Regression Deletion Diagnostics
rstudent.deconv | Regression Deletion Diagnostics
scapply | Single-cell apply a function to a matrix split by a factor
scmean | Single-cell mean log gene expression across cell types
se | Standard errors of deconvoluted cell counts
shift_noise | Add noise to count data
signature_heatmap | Gene signature heatmap
simulate_bulk | Simulate pseudo-bulk RNA-Seq
slapply | Apply a function to a big matrix by slicing
specificity_plot | Specificity plot
specificity_plotly | Specificity plot
spillover_heatmap | Spillover heatmap
sqrt_noise | Add noise to count data
stack_ggplot | Stacked bar plot
stack_plot | Stacked bar plot
summary.tune_deconv | Summarising deconvolution tuning
trimmean | Mean Objects
tune_deconv | Tune deconvolution parameters
updateMarkers | Update cellMarkers object
violin_plot | Cell subclass violin plot