CorAnalysis: CorAnalysis:

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

Description

Ranks correlation between a given gene and all other genes in a dataset. Plots both the given gene and highly correlated genes for a given correlation value

Usage

CorAnalysis(
  genename,
  dataset,
  threshold = 0.9,
  average = "mean",
  lag = 0,
  save = FALSE,
  print = TRUE,
  df = TRUE
)

Arguments

genename	the name of a gene intended for comparison with all other genes in the dataset. Must be a string.
dataset	A transcriptomics dataset. First columns should be gene names. All other columns should be expression levels.
threshold	Set correlation threshold value for which genes are considered significant and thus plotted. Defaults to 0.9
average	The average to be used for comparing the time points. Either 'median' or 'mean'.
lag	Setting any value other than 0 allows a gene to be correlated with lagged genes in the dataset. The number denotes the number of timesteps to lag by.
save	Logical. If TRUE, saves plots to working directory. Defaults to FALSE.
print	Logical. If TRUE renders highly correlated genes in the plot viewer. Defaults to TRUE
df	Logical. If TRUE a dataframe containing the correlations of the given gene with all genes in the dataset is returned. Defaults to TRUE.

Value

Prints or saves ggplot2 object(s). Optionally returns dataframe containing gene names and correlation values

Examples

cor_results <- CorAnalysis('comp100002_c0_seq2', Laurasmappings)

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