switchde: Switch-like model fitting and differential expression test

Description Usage Arguments Value Examples

View source: R/switchde.R

Description

Fit sigmoidal differential expression models to gene expression across pseudotime. Parameter estimates are returned along with a p-value for switch-like differential expression over a null model (constant expression).

Usage

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switchde(object, pseudotime = NULL, zero_inflated = FALSE,
  lower_threshold = 0.01, maxiter = 1000, log_lik_tol = 0.01,
  verbose = FALSE, sce_assay = "exprs")

Arguments

object

Gene expression data that is either

  • A vector of length number of cells for a single gene

  • A matrix of dimension number of genes x number of cells

  • An object of class SingleCellExperiment from package SingleCellExperiment

pseudotime

A pseudotime vector with a pseudotime corresponding to every cell. Can be NULL if object is of class SCESet and colData(sce)$pseudotime is defined.

zero_inflated

Logical. Should zero inflation be implemented? Default FALSE

lower_threshold

The minimum threshold below which to set expression to zero to avoid numerical issues. Default is 0.01

maxiter

Maximum number of iterations for EM algorithm if zero inflation enabled. Default 100

log_lik_tol

If the change in the log-likelihood falls below this for zero inflated EM the algorithm is assumed to have converged

verbose

Print convergence update for EM algorithm

sce_assay

The assay from the SingleCellExperiment to be used as expression, defaulting to "exprs"

Value

A matrix where each column corresponds to a gene, the first row is the p-value for that gene and subsequent rows are model parameters.

Examples

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switchde documentation built on Nov. 8, 2020, 5:19 p.m.