dataframe containing spot type specifiers, usually input using readSpotTypes.
genes
dataframe containing gene annotation, or an object of class RGList, MAList, EListRaw, EList or MArrayLM from which the gene annotation can be extracted.
spottypecol
integer or name specifying column of types containing spot type names.
regexpcol
vector of integers or column names specifying columns of types containing regular expressions.
Defaults to any column names in common between types and genes.
verbose
logical, if TRUE then progess on pattern matching is reported to the standard output channel.
Details
This function constructs a vector of status codes by searching for patterns in the gene list.
The data frame genes contains gene IDs and should have as many rows as there are spots on the microarrays.
Such a data frame is often read using readGAL.
The data frame types has as many rows as you want to distinguish types of spots in the gene list.
This data frame should contain a column or columns, the regexpcol columns, which have the same names as columns in genes and which contain patterns to match in the gene list.
Another column, the spottypecol, contains the names of the spot types.
Any other columns are assumed to contain plotting parameters, such as colors or symbols, to be associated with the spot types.
The patterns in the regexpcol columns are simplified regular expressions.
For example, AA* means any string starting with AA, *AA means any code ending with AA, AA means exactly these two letters, *AA* means any string containing AA, AA. means AA followed by exactly one other character and AA. means exactly AA followed by a period and no other characters.
Any other regular expressions are allowed but the codes ^ for beginning of string and $ for end of string should not be included.
Note that the patterns are matched sequentially from first to last, so more general patterns should be included first.
For example, it is often a good idea to include a default spot-type as the first line in types with pattern * for all regexpcol columns and default plotting parameters.
Value
Character vector specifying the type (or status) of each spot on the array.
Attributes contain plotting parameters associated with each spot type.
Author(s)
Gordon Smyth
See Also
An overview of LIMMA functions for reading data is given in 03.ReadingData.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(limma)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/limma/controlStatus.Rd_%03d_medium.png", width=480, height=480)
> ### Name: controlStatus
> ### Title: Set Status of each Spot from List of Spot Types
> ### Aliases: controlStatus
> ### Keywords: IO
>
> ### ** Examples
>
> genes <- data.frame(
+ ID=c("Control","Control","Control","Control","AA1","AA2","AA3","AA4"),
+ Name=c("Ratio 1","Ratio 2","House keeping 1","House keeping 2",
+ "Gene 1","Gene 2","Gene 3","Gene 4"))
> types <- data.frame(
+ SpotType=c("Gene","Ratio","Housekeeping"),
+ ID=c("*","Control","Control"),
+ Name=c("*","Ratio*","House keeping*"),
+ col=c("black","red","blue"))
> status <- controlStatus(types,genes)
Matching patterns for: ID Name
Found 8 Gene
Found 2 Ratio
Found 2 Housekeeping
Setting attributes: values col
>
>
>
>
>
> dev.off()
null device
1
>