efroni_mean: Compute mean expression for each cell type (Efroni method)

In b-coli/ICITools: R Implementation of Tools for Calculating the Index of Cell Identity

Description

Uses the Efroni method to compute mean expression for each cell type present in 'expression_data'. Here, it computes the mean expression, divided by the "binsize" used to classify expression.

Usage

efroni_mean(expression_data)

Arguments

expression_data

data frame (or tibble) minimally containing the following columns for a single locus Expression (the normalized expression value, not log-transformed) Cell_Type (the cell type from which the expression data came from) binsize (the optimized binsize used to compute expression bins)

Value

a data frame (or tibble) containing the summarized mean and median expression values for each cell type.

References

Ifroni, E., Ip, PL., Nawy, T., Mello, A., Birnbaum, KD. 2015. "Quantification of cell identity from single-cell gene expression profiles". Genome Biology 16(9)

Birnbaum, KD. and Kussell, E. 2011. "Measuring cell identity in noisy biological systems". Nucl. Acids. Res. 39(21)

b-coli/ICITools documentation built on Dec. 27, 2021, 7:40 a.m.