fitNBtb: Function for fitting a negative binomial noise model of...

In RaceID: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Function for fitting a negative binomial noise model of technical and biological variability

Description

This function fits a negative binomial model to transcript counts of a group of cells thereby deconvoluting variability into sampling noise, global cell-to-cell variability of transcript counts, and residual variability, which corresponds to biological noise.

Usage

fitNBtb(z, gamma = 2, x0 = 0, lower = 0, upper = 100, grad = TRUE)

Arguments

z	Transcript count matrix with cells as columns and genes as rows.
gamma	Positive real number. Scale paramter of the cauchy prior. Default is 2.
x0	Real number greater or equal to zero. Location parameter of the cauchy prior.
lower	Real number greater or equal to zero. Lower bound for the maximum a posterior inference of the biological noise. Default is 0.
upper	Real number greater or equal to zero. Upper bound for the maximum a posterior inference of the biological noise. Default is 100.
grad	Logical. If TRUE then maximum a posterior value is inferred by determining the root of the gradient function. Otherwise, the maximum of the posterior probability is determined numerically. Default is TRUE.

Value

Data.frame with four columns:

mu	Mean expression.
epsilon	Biological noise.
rt	Dispersion parameter capturing global cell-to-cell variability of transcript counts.
alphaG	Dispersion parameter capturing global cell-to-cell variability of transcript counts and biological noise.

RaceID documentation built on Sept. 28, 2023, 5:06 p.m.