ELBOW (version 1.8.0)

analyze_elbow: extracts all elbow statistics and plots and elbow curve.

Description

Analyzes:

• the Elbow cut-offs
• the Elbow curve variance
• the upper and lower error Elbow curves
• $\log\chi^2$ p-value for the Elbow curve model

Usage

analyze_elbow(probes, initial_conditions, final_conditions, gtitle = "")

Arguments

probes

the data set of probes (as a data.frame).

initial_conditions

a 2D data.fram containing all of the replicate gene expression values corresponding to the experiment's initial conditions.

final_conditions

a 2D data.fram containing all of the replicate gene expression values corresponding to the experiment's final conditions.

gtitle

the title to display for the graph.

Value

a list of all significant probes

Details

Then plots the data to a curve - AND - prints the statistics to both the terminal and the plot canvas.

Examples

# read in the EcoliMutMA sample data from the package
		data(EcoliMutMA, package="ELBOW")
		csv_data <- EcoliMutMA
		# - OR - Read in a CSV file (uncomment - remove the #'s
		#        - from the line below and replace 'filename' with
		#        the CSV file's filename)
		# csv_data <- read.csv(filename)

		# set the number of initial and final condition replicates both to three
		init_count  <- 3
		final_count <- 3

		# Parse the probes, intial conditions and final conditions
		# out of the CSV file.  Please see: extract_working_sets
		# for more information.
		#
		# init_count should be the number of columns associated with
		#       the initial conditions of the experiment.
		# final_count should be the number of columns associated with
		#       the final conditions of the experiment.
		working_sets <- extract_working_sets(csv_data, init_count, final_count)

		probes <- working_sets[[1]]
		initial_conditions <- working_sets[[2]]
		final_conditions <- working_sets[[3]]

		# Uncomment to output the plot to a PNG file (optional)
		# png(file="output_plot.png")

		# Analyze the elbow curve.
		sig <- analyze_elbow(probes, initial_conditions, final_conditions)

		# write the significant probes to 'signprobes.csv'
		write.table(sig,file="signprobes.csv",sep=",",row.names=FALSE)