DRomics (version 2.1-3)

continuousanchoringdata: Import and check of continuous anchoring apical data

Description

Continuous anchoring apical data are imported from a .txt file (internally imported using the function read.table) and checked or from a R object of class data.frame (see the description of argument file for the required format of data). No transformation is provided in this function. If needed the pretreatment of data must be done before importation of data, so that they can be directly modelled using a Gaussian error model. This strong hypothesis is required both for selection of responsive endpoints and for dose-reponse modelling.

Usage

continuousanchoringdata(file, check = TRUE)
# S3 method for continuousanchoringdata
print(x, …)
# S3 method for continuousanchoringdata
plot(x, …)

Arguments

file

The name of the .txt file (e.g. "mydata.txt") containing one row per endpoint, with the first column corresponding to the identifier of each endpoint, and the other columns giving the measured values of the endpoint for each replicate at each dose or concentration. In the first line, after a name for the endpoint column, we must have the tested doses or concentrations in a numeric format for the corresponding replicate (for example, if there are triplicates for each treatment, the first line could be "endpoint", 0, 0, 0, 0.1, 0.1, 0.1, etc.). This file is imported within the function using the function read.table with its default field separator (sep argument). Alternatively an R object of class data.frame can be directly given in input, corresponding to the output of read.table(file, header = FALSE) on a file described as above. The two alternatives are illustrated below in examples.

check

If TRUE the format of the input file is checked.

x

An object of class "continuousanchoringdata".

…

further arguments passed to print or plot functions.

Value

continuousanchoringdata returns an object of class "continuousanchoringdata", a list with 5 components:

data

the numeric matrix of responses of each item in each replicate (one line per item, one column per replicate)

dose

the numeric vector of the tested doses or concentrations corresponding to each column of data

item

the character vector of the identifiers of the endpoints, corresponding to each line of data

design

a table with the experimental design (tested doses and number of replicates for each dose) for control by the user

data.mean

the numeric matrix of mean responses of each item per dose (mean of the corresponding replicates) (one line per item, one column per unique value of the dose

The print of a continuousanchoringdata object gives the tested doses (or concentrations) and number of replicates for each dose, the number of items, the identifiers of the first 20 items (for check of good coding of data) and the normalization method. The plot of a continuousanchoringdata object shows the data distribution for each dose or concentration and replicate.

Details

This function imports the data, checks their format (see the description of argument file for the required format of data) and gives in the print information that should help the user to check that the coding of data is correct : the tested doses (or concentrations) the number of replicates for each dose, the number of endpoints.

See Also

See read.table the function used to import data, and microarraydata, RNAseqdata and microarraydata for other types of data.

Examples

# NOT RUN {
# (1) import and check of continuous anchoring data 
# (an example with two apical endpoints of an example given in the package (see ?Scenedesmus))
#
datafilename <- system.file("extdata", "apical_anchoring.txt", package = "DRomics")

o <- continuousanchoringdata(datafilename, check = TRUE)
print(o)
# }
# NOT RUN {
plot(o)
# }
# NOT RUN {
# If you want to use your own data set just replace datafilename, 
# the first argument of continuousanchoringdata(), 
# by the name of your data file (e.g. "mydata.txt")
# 
# You should take care that the field separator of this data file is one
# of the default field separators recognised by the read.table() function
# when it is used with its default field separator (sep argument)
# Tabs are recommended.

# Use of an R object of class data.frame
# on the same example (see ?Scenedesmus for details)
data(Scenedesmus_apical)
o <- continuousanchoringdata(Scenedesmus_apical)
print(o)
# }
# NOT RUN {
plot(o)
# }
# NOT RUN {

# }