limma (version 3.28.14)

detectionPValues: Detection P-Values from Negative Controls

Description

Compute the proportion of negative controls greater than each observed expression value. Particularly useful for Illumina BeadChips.

Usage

"detectionPValues"(x, status = NULL, ...)
"detectionPValues"(x, status, negctrl = "negative", ...)

Arguments

x

object of class EListRaw or a numeric matrix containing raw intensities for regular and control probes from a series of microarrays.

status

character vector giving probe types. Defaults to x$genes$Status if x is an EListRaw object.

negctrl

character string identifier for negative control probes.

...

other arguments are not currently used.

Value

x containing detection p-values.

Details

The rows of x for which status == negctrl are assumed to correspond to negative control probes.

For each column of x, the detection p-values are defined as (N.eq/2 + N.gt) / N.neg, where N.gt is the number of negative controls with expression greater than the observed value, N.eq is the number of negative controls with expression equal to the observed value, and N.neg is the total number of negative controls.

References

Shi, W, de Graaf, C, Kinkel, S, Achtman, A, Baldwin, T, Schofield, L, Scott, H, Hilton, D, Smyth, GK (2010). Estimating the proportion of microarray probes expressed in an RNA sample. Nucleic Acids Research 38, 2168-2176. http://nar.oxfordjournals.org/content/38/7/2168

See Also

An overview of LIMMA functions to read expression data is given in 03.ReadingData.

read.idat reads Illumina BeadChip expression data from binary IDAT files.

neqc performs normexp background correction and quantile normalization aided by control probes.

Examples

## Not run: 
# # Read Illumina binary IDAT files
# x <- read.idat(idat, bgx)
# x$genes$DectionPValue <- detectionPValues(x)
# y <- neqc(x)
# ## End(Not run)

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