get_enc: Calculate effective number of codons (ENC)

In cubar: Codon Usage Bias Analysis

Calculate effective number of codons (ENC)

Description

get_enc computes the effective number of codons (ENC) for each coding sequence, which quantifies the degree of codon usage bias. Lower ENC values indicate stronger bias (fewer codons are used), while higher values indicate more uniform codon usage.

Usage

get_enc(cf, codon_table = get_codon_table(), level = "subfam")

Arguments

cf	A matrix of codon frequencies as calculated by count_codons(). Rows represent sequences and columns represent codons.
codon_table	A codon table defining the genetic code, derived from get_codon_table() or create_codon_table().
level	Character string specifying the analysis level: "subfam" (default, analyzes codon subfamilies) or "amino_acid" (analyzes at amino acid level).

Value

A named numeric vector of ENC values. Names correspond to sequence identifiers from the input matrix. ENC values typically range from 20 (maximum bias) to 61 (uniform usage).

References

Wright F. 1990. The 'effective number of codons' used in a gene. Gene 87:23-29.

Sun X, Yang Q, Xia X. 2013. An improved implementation of effective number of codons (NC). Mol Biol Evol 30:191-196.

Examples

# Calculate ENC for yeast genes
cf_all <- count_codons(yeast_cds)
enc <- get_enc(cf_all)
head(enc)
hist(enc, main = "Distribution of ENC values")

cubar documentation built on Aug. 21, 2025, 5:40 p.m.