aggregateData: Averages photographs of the same type

In acgerstein/diskImageR: A Pipeline to Analyze Resistance and Tolerance from Drug Disk Diffusion Assays

Averages photographs of the same type

Description

Uses a user-supplied variance measure (currently supported: standard error, coefficient of variation, built-in R functions (e.g., sd) to calculate variance among photographs of the same type

Usage

aggregateData(
  projectName,
  varFunc = "se",
  replicate = c("line", "type"),
  overwrite = TRUE,
  save = TRUE
)

Arguments

projectName	the short name in use for the project.
varFunc	what type of variation measurment to perform. Currently supports varFunc = "se" to calculate the standard error, varFun = "cv" to calculate the coefficient of variation or any built-in R function (e.g., sd).
replicate	a character vector indicating which the column names that contain which factors to use. Defaults to c("line", "type"). Note that if the typeVector name was changed in createDataframe this should be reflected here.
overwrite	a logical value indicating whether to overwrite existing aggregate dataframe for the same project name. This allows you to save different dataframes averaging across different factors or using different variance measures
save	denotes whether to overwrite the existing .csv file or just update the .df in the R global environment. Defaults to TRUE.

Value

A dataframe "projectName.ag" is saved to the global environment and a .csv file "projectName_ag.csv" is exported to the "parameter_files" directory.

See Also

addType if there multiple factors in your experiment. Add whatever the new factor is called (default: "type2") to the replicate vector if this is appropriate.

Examples

## Not run: 
aggregateData("myProject")
aggregateData("myProject", varFunc= "sd", replicate = c("line", "drugAmt"), overwrite = FALSE)

## End(Not run)

acgerstein/diskImageR documentation built on July 18, 2024, 1:47 p.m.