CosinorAnalysis: CosinorAnalysis:

In nathansam/CircadianTools: Collection of Tools for Detecting Rhythmic Genes

Description

Fits cosinor models to transcriptomics data and plots the best-fitting models using ggplot2.

Usage

CosinorAnalysis(
  dataset,
  period = 24,
  timelag = 6,
  threshold = 0.05,
  adj = "bonferroni",
  progress = TRUE,
  save = FALSE,
  print = TRUE,
  df = TRUE
)

Arguments

dataset	A transcriptomics dataset. First columns should be gene names. All other columns should be expression levels.
period	The period of rhythmicity which is being tested for. Defaults to 24 (circadian).
timelag	The value of time for which observations begin. Defaults to 6.
threshold	Set significance value for which genes are considered significant and thus plotted. Defaults to 6e-07.
adj	String. p-value adjustment. Defaults to 'bonferonni'. 'none' is also supported.
progress	Logical. If TRUE then a loading bar will be printed to denote progress.
save	Logical. If TRUE, saves plots to working directory. Defaults to FALSE.
print	Logical. If TRUE renders significant genes in the plot viewer. Defaults to TRUE.
df	Logical. If TRUE a dataframe containing the results of the cosinor analysis will be returned. Defaults to TRUE.

Value

Prints or saves ggplot2 object(s). Optionally returns dataframe containing gene name and p values from F-test ranking of cosinor models.

Examples

cosinor_results <- CosinorAnalysis(Laurasmappings)

nathansam/CircadianTools documentation built on Dec. 26, 2019, 11:30 a.m.