CVRCFunc

CVRCFunc is a lightweight R package for CVRC single-cell analysis helpers. It contains pseudobulk differential expression wrappers and plotting helpers built around Seurat, DESeq2, and ggplot2.

Installation

Install from GitHub:

if (!requireNamespace("devtools", quietly=TRUE)) install.packages("devtools")
devtools::install_github("mgildea87/CVRCFunc")

Install locally from source:

devtools::install_local("/path/to/CVRCFunc")

Main functions

FindMarkersBulk()

Performs pseudobulk differential expression for every cluster using sample-level aggregation and DESeq2.

• seurat: a Seurat object.
• clus_ident: cluster identity column in seurat@meta.data.
• sample_ident: sample identifier column used for pseudobulking.
• optional batch_var, covariates, or custom design_formula.
• outputs CSV and PDF QC files into out_dir.
• optionally writes runtime messages and warnings to a log file via log_file.

FindMarkersCondition()

Runs pseudobulk DE per cluster between two conditions.

• condition_ident: metadata column defining condition labels.
• conditions: a length-two vector of condition values, e.g. c("treated", "control").
• positive log2FC means higher expression in conditions[1].
• supports batch_var, covariates, and custom design_formula.
• use test_type = "LRT" for likelihood ratio tests or test_type = "Wald" for Wald tests.
• with test_type = "LRT", the function uses a reduced model automatically when no custom design is provided. The reduced design will be the full design without condition_ident. If conditions == NULL (default) test will be run including all levels of condition_ident. Otherwise data will be subset to the 2 specified levels of condition_ident.
• LRT output uses the raw DESeq2 log2FC as the main log2FoldChange column, does not add a separate log2FoldChange_raw column, and adds one log2FoldChange_<coef_name> column per condition coefficient.

FindMarkers()

Compares two groups of cells defined by a metadata identity.

• group_1 and group_2 are values from clus_ident.
• sample_ident controls pseudobulk aggregation.
• useful for pairwise cluster/group comparisons.

BetterVlnPlot()

Creates refined violin plots for feature expression from a Seurat object.

• supports optional condition_ident to split by condition.
• accepts idents_to_plot, ncol, dot_size, and y_axis_title.
• returns a ggplot2 object.

Example usage

library(CVRCFunc)
# Bulk cluster DEbulk_res<- FindMarkersBulk(
seurat=seu,
clus_ident="seurat_clusters",
sample_ident="sample_id",
batch_var="batch",
covariates= c("age", "sex"),
out_dir="FindMarkersBulk_output",
log_file= file.path("FindMarkersBulk_output", "analysis.log")
)
# Condition DE within clusters (LRT)cond_res<- FindMarkersCondition(
seurat=seu,
clus_ident="seurat_clusters",
sample_ident="sample_id",
condition_ident="condition",
conditions= c("treated", "control"),
out_dir="FindMarkersCondition_output",
test_type="LRT"
)
# Condition DE within clusters (Wald)cond_res_wald<- FindMarkersCondition(
seurat=seu,
clus_ident="seurat_clusters",
sample_ident="sample_id",
condition_ident="condition",
conditions= c("treated", "control"),
out_dir="FindMarkersCondition_output_wald",
test_type="Wald"
)
# Condition DE with custom full and reduced designsfull_design<-~condition+batch+age+sexreduced_design<-~batch+age+sexcond_res_design<- FindMarkersCondition(
seurat=seu,
clus_ident="seurat_clusters",
sample_ident="sample_id",
condition_ident="condition",
conditions= c("treated", "control"),
design_formula=full_design,
out_dir="FindMarkersCondition_output_design",
test_type="LRT"
)
# Pairwise group comparisonpair_res<- FindMarkers(
seurat=seu,
clus_ident="seurat_clusters",
group_1="0",
group_2="1",
sample_ident="sample_id",
batch_var="batch",
out_dir="FindMarkers_output"
)
# Better violin plotp<- BetterVlnPlot(
seurat=seu,
clus_ident="seurat_clusters",
features= c("CD3D", "GNLY"),
assay="RNA",
condition_ident="treatment",
ncol=2,
dot_size=0.5
)
print(p)

Notes

• Requires Seurat, DESeq2, ggplot2, pheatmap, tidyr, ggbeeswarm, and related packages.
• Functions create output directories automatically when needed.