DRomics (version 2.1-3)

microarraydata: Import, check and normalization of single-channel microarray data

Description

Single-channel microarray data in log2 are imported from a .txt file (internally imported using the function read.table), checked or from a R object of class data.frame (see the description of argument file for the required format of data)and normalized (between arrays normalization). omicdata is a deprecated version of microarraydata.

Usage

microarraydata(file, check = TRUE, 
  norm.method = c("cyclicloess", "quantile", "scale", "none"))
  
omicdata(file, check = TRUE, 
  norm.method = c("cyclicloess", "quantile", "scale", "none"))
# S3 method for microarraydata
print(x, …)
# S3 method for microarraydata
plot(x, …)

Arguments

file

The name of the .txt file (e.g. "mydata.txt") containing one row per item, with the first column corresponding to the identifier of each item, and the other columns giving the responses of the item for each replicate at each dose or concentration. In the first line, after a name for the identifier 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 "item", 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.

check

If TRUE the format of the input file is checked.

norm.method

If "none" no normalization is performed, else a normalization is performed using the function normalizeBetweenArrays of the limma package using the specified method.

x

An object of class "microarraydata".

…

further arguments passed to print or plot functions.

Value

microarraydata returns an object of class "microarraydata", a list with 7 components:

data

the numeric matrix of normalized 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 items, 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

norm.method

The normalization method specified in input

data.beforenorm

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

The print of a microarraydata 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 microarraydata object shows the data distribution for each dose or concentration and replicate before and after normalization.

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 items, the identifiers of the first 20 items. If the argument norm.method is not "none", data are normalized using the function normalizeBetweenArrays of the limma package using the specified method : "cyclicloess" (default choice), "quantile" or "scale".

References

Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, and Smyth, GK (2015), limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43, e47.

See Also

See read.table the function used to import data, normalizeBetweenArrays for details about the normalization and RNAseqdata and metabolomicdata for other types of data.

Examples

# NOT RUN {
# (1) import, check and normalization of microarray data 
# (an example on a subsample of a greater data set published in Larras et al. 2018
# Transcriptomic effect of triclosan in the chlorophyte Scenedesmus vacuolatus)
#
datafilename <- system.file("extdata", "transcripto_very_small_sample.txt", 
  package="DRomics")
o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
print(o)
plot(o)

# If you want to use your own data set just replace datafilename, 
# the first argument of microarraydata(), 
# 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.

# }
# NOT RUN {
# (2) normalization with other methods
(o.2 <- microarraydata(datafilename, check = TRUE, norm.method = "quantile"))
plot(o.2)
(o.3 <- microarraydata(datafilename, check = TRUE, norm.method = "scale"))
plot(o.3)

# }