plot_elbow {ELBOW} | R Documentation

## plots Elbow curve data.

### Description

Plots an elbow curve and its associated data:

- the upper and lower elbow limits for the curve

- the upper, lower, and median initial condition Elbow plots

- the \logχ^2 p-value for the Elbow curve

- the variance for the upper and lower Elbow cut-off values

### Usage

      plot_elbow(my_data, upper_limit, lower_limit, pvalue1,
        prowmin, prowmax, prowmedian, max_upper_variance,
        min_upper_variance, max_lower_variance,
        min_lower_variance, gtitle = "")

### Arguments

`my_data` | A table (data.frame) to plot. The columns in the table should be as follows: probes — one column containing the names of the probes fold — the fold values for the table
`upper_limit` | the upper limit/cut-off for the elbow.
`lower_limit` | the lower limit/cut-off for the elbow.
`pvalue1` | the \logχ^2 p-value for the elbow curve.
`prowmin` | the error limit based on the maximum value for each probe.
`prowmax` | the error limit based on the minimum value for each probe.
`prowmedian` | the null (median) value for each probe.
`max_upper_variance` | the maximum upper elbow limit (most positive).
`min_upper_variance` | the minimum upper elbow limit.
`max_lower_variance` | the maximum lower elbow limit.
`min_lower_variance` | the minimum lower elbow limit (most negative).
`gtitle` | the title to display for the graph.

### 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")

    		my_data <- replicates_to_fold(probes, initial_conditions, final_conditions)

    		# compute the elbow for the dataset
    		limits <- do_elbow(data.frame(my_data$fold))

    		plus_minus <- elbow_variance(probes, initial_conditions, final_conditions)

    		max_upper_variance <- plus_minus$max_upper
    		min_upper_variance <- plus_minus$min_upper
    		max_lower_variance <- plus_minus$max_lower
    		min_lower_variance <- plus_minus$min_lower

    		# rounded number for nice appearance graph
    		upper_limit <- round(limits[[1]],digits=2)

    		# rounded number nice appearance for graph
    		lower_limit <- round(limits[[2]],digits=2)

    		p_limits <- null_variance(my_data, upper_limit, lower_limit, initial_conditions)

    		prowmin <- p_limits[[1]]
    		prowmax <- p_limits[[2]]
    		prowmedian <- p_limits[[3]]

    		pvalue1 <- get_pvalue(my_data, upper_limit, lower_limit)
    		plot_elbow(my_data, upper_limit, lower_limit, pvalue1, prowmin, prowmax, prowmedian, max_upper_variance, min_upper_variance, max_lower_variance, min_lower_variance, "Title of the ELBOW Plot")

[Package ELBOW version 1.16.0 Index]