R: Combines features in an 'MSnSet' object

combineFeatures {MSnbase}

R Documentation

Combines features in an `MSnSet` object

Description

This function combines the features in an "MSnSet" instance applying a summarisation function (see fun argument) to sets of features as defined by a factor (see groupBy argument). Note that the feature names are automatically updated based on the groupBy parameter.

The coefficient of variations are automatically computed and collated to the featureData slot. See cv and cv.norm arguments for details.

NB: All the functions available as fun take a na.rm argument. This argument is FALSE by default. This will have as effect that NA get propagated at the higher level. It is generally advised to set na.rm = TRUE. See the example below.

Usage


combineFeatures(object, groupBy, fun = c("mean", "median",
"weighted.mean", "sum", "medpolish", "iPQF", "NTR"), redundancy.handler =
c("unique", "multiple"), cv = TRUE, cv.norm = "sum", verbose =
isMSnbaseVerbose(), ...)

Arguments

`object`	An instance of class `"MSnSet"` whose features will be summerised.
`groupBy`	A `factor`, `character`, `numeric` or a `list` of the above defining how to summerise the features. The list must be of length `nrow(object)`. Each element of the list is a vector describing the feature mapping. If the list can be named, its names must match `fetureNames(object)`. See `redundancy.handler` for details about the latter.
`fun`	The summerising function. Currently, mean, median, weighted mean, sum, median polish, iPQF (see `iPQF` for details) and NTR (see `NTR` for details) are implemented, but user-defined functions can also be supplied.
`redundancy.handler`	If `groupBy` is a `list`, one of `"unique"` (default) or `"multiple"` (ignored otherwise) defining how to handle peptides that can be associated to multiple higher-level features (proteins) upon combination. Using `"unique"` will only consider uniquely matching features (features matching multiple proteins will be discarded). `"multiple"` will allow matching to multiple proteins and each feature will be repeatedly tallied for each possible matching protein.
`cv`	A `logical` defining if feature coefficients of variation should be computed and stored as feature meta-data. Default is `TRUE`.
`cv.norm`	A `character` defining how to normalise the feature intensitites prior to CV calculation. Default is `sum`. Use `none` to keep intensities as is. See `featureCV` for more details.
`verbose`	A `logical` indicating whether verbose output is to be printed out.
`...`	Additional arguments for the `fun` function.

Value

A new "MSnSet" instance is returned with ncol (i.e. number of samples) is unchanged, but nrow (i.e. the number od features) is now equals to the number of levels in groupBy. The feature metadata (featureData slot) is updated accordingly and only the first occurrence of a feature in the original feature meta-data is kept.

Author(s)

Laurent Gatto <lg390@cam.ac.uk>

References

iPQF: a new peptide-to-protein summarization method using peptide spectra characteristics to improve protein quantification. Fischer M, Renard BY. Bioinformatics. 2016 Apr 1;32(7):1040-7. doi:10.1093/bioinformatics/btv675. Epub 2015 Nov 20. PubMed PMID:26589272.

Examples

data(msnset)
msnset <- msnset[11:15, ]
exprs(msnset)

## arbitrary grouping into two groups
grp <- as.factor(c(1, 1, 2, 2, 2))
msnset.comb <- combineFeatures(msnset, grp, "sum")
dim(msnset.comb)
exprs(msnset.comb)
fvarLabels(msnset.comb)

## grouping with a list
grpl <- list(c("A", "B"), "A", "A", "C", c("C", "B"))
## optional naming
names(grpl) <- featureNames(msnset)
exprs(combineFeatures(msnset, grpl, fun = "sum", redundancy.handler = "unique"))
exprs(combineFeatures(msnset, grpl, fun = "sum", redundancy.handler = "multiple"))

## missing data
exprs(msnset)[4, 4] <-
    exprs(msnset)[2, 2] <- NA
exprs(msnset)
## NAs propagate in the 115 and 117 channels
exprs(combineFeatures(msnset, grp, "sum"))
## NAs are removed before summing
exprs(combineFeatures(msnset, grp, "sum", na.rm = TRUE))

## using iPQF
data(msnset2)
res <- combineFeatures(msnset2,
                       groupBy = fData(msnset2)$accession,
                       redundancy.handler = "unique",
                       fun = "iPQF",
                       low.support.filter = FALSE,
                       ratio.calc = "sum",
                       method.combine = FALSE)
head(exprs(res))

[Package MSnbase version 2.4.2 Index]

Combines features in an MSnSet object