logLikelihoodcelda_C {celda}R Documentation

Calculate Celda_C log likelihood

Description

Calculates the log likelihood for user-provided cell population clusters using the 'celda_C()' model.

Usage

logLikelihoodcelda_C(counts, sampleLabel, z, K, alpha, beta)

Arguments

counts

Integer matrix. Rows represent features and columns represent cells.

sampleLabel

Vector or factor. Denotes the sample label for each cell (column) in the count matrix.

z

Numeric vector. Denotes cell population labels.

K

Integer. Number of cell populations.

alpha

Numeric. Concentration parameter for Theta. Adds a pseudocount to each cell population in each sample. Default 1.

beta

Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature in each cell population. Default 1.

Value

Numeric. The log likelihood for the given cluster assignments

See Also

'celda_C()' for clustering cells

Examples

data(celdaCSim)
loglik <- logLikelihoodcelda_C(celdaCSim$counts,
    sampleLabel = celdaCSim$sampleLabel,
    z = celdaCSim$z,
    K = celdaCSim$K,
    alpha = celdaCSim$alpha,
    beta = celdaCSim$beta)

loglik <- logLikelihood(celdaCSim$counts,
    model = "celda_C",
    sampleLabel = celdaCSim$sampleLabel,
    z = celdaCSim$z,
    K = celdaCSim$K,
    alpha = celdaCSim$alpha,
    beta = celdaCSim$beta)

[Package celda version 1.2.4 Index]