gene_angle: Vector based best marker selection

In cellGeometry: Geometric Single Cell Deconvolution

Vector based best marker selection

Description

Core function which takes a matrix of mean gene expression (assumed to be log2 transformed to be more Gaussian). Mean gene expression per gene is scaled to a unit hypersphere assuming each gene represents a vector in space with dimensions representing each cell subclass/group.

Usage

gene_angle(genemeans)

Arguments

genemeans

matrix of mean gene expression with genes in rows and celltypes, tissues or subclasses in columns.

Value

a list whose length is the number of columns in genemeans, with each element containing a dataframe with genes in rows, sorted by best marker status as determined by minimum vector angle and highest maximum gene expression per celltype/tissue.

cellGeometry documentation built on April 20, 2026, 1:06 a.m.