getDEG.Rd
Differential expression analysis wrapper for presto::wilcoxauc(). Option to return differentially-expressed gene list (return.list = T) or statistics only (return.list = F)
getDEG(
object,
assay = DefaultAssay(object),
data = "data",
group_by = "seurat_clusters",
auc.thresh = 0.6,
fdr.thresh = 0.01,
logFC.thresh = NA,
pct.dif.thresh = NA,
pct.in.thresh = NA,
pct.out.thresh = NA,
return.list = F,
return.all = F,
sig.figs = NA,
verbose = T
)
Seurat object
assay. Default "SCT".
data slot. Default "data".
Name of grouping variable (must be present in object's meta.data)
AUC threshold. Default = 0.6.
FDR threshold. Default = 0.01.
logFC threshold. Default = NA.
Difference in expression percentage. Default = NA.
Expression percentages exceeding this threshold are retained. Default is NA.
Expression percentages below this threshold are retained Default is NA.
If TRUE, return list of differentially expressed genes. If FALSE, returns table with statistics from differential expression analysis.
If TRUE, all thresholding filters are ignored, and all results are returned.
If specified and return.list = F, rounds statistics to specified significant figure (recommended: 3). Default is NA.
Print progress. Default is TRUE.
data.frame or list. Statistics in data.frame output include:
avgExpr: Average expression for group
logFC: Log fold change
statistics: Test statistics
auc: Area under curve
pval: p-value
padj: adjusted p-value
pct_in: percentage of expressing cells within group
pct_out: percentage of expression cells outside of group
pct.dif: difference between pct_in and pct_out
sensitivity: pct_in/100
specificity: (100-pct_out)/100
PPV: positive predictive value
NPV: negative predictive value
ss: sensitivity x specificity
wilcoxauc