analyze_elbow {ELBOW} | R Documentation |
Analyzes:
the Elbow cut-offs
the Elbow curve variance
the upper and lower error Elbow curves
\logχ^2 p-value for the Elbow curve model
analyze_elbow(probes, initial_conditions, final_conditions, gtitle = "")
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. |
Then plots the data to a curve - AND - prints the statistics to both the terminal and the plot canvas.
a list of all significant probes
# 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)