Identify aggregation outliers
This function evaluates the variability within all protein group
of an MSnSet. If a protein group is composed only of a
single feature, NA is returned.
aggvar(object, groupBy, fun)
object |
An object of class |
groupBy |
A |
fun |
A function the summarise the distance between features
within protein groups, typically |
This function can be used to identify protein groups with
incoherent feature (petides or PSMs) expression patterns. Using
max as a function, one can identify protein groups with
single extreme outliers, such as, for example, a mis-identified
peptide that was erroneously assigned to that protein group. Using
mean identifies more systematic inconsistencies where, for
example, the subsets of peptide (or PSM) feautres correspond to
proteins with different expression patterns.
A matrix providing the number of features per
protein group (nb_feats column) and the aggregation
summarising distance (agg_dist column).
Laurent Gatto
combineFeatures to combine PSMs
quantitation into peptides and/or into proteins.
library("pRolocdata")
data(hyperLOPIT2015ms3r1psm)
groupBy <- "Protein.Group.Accessions"
res1 <- aggvar(hyperLOPIT2015ms3r1psm, groupBy, fun = max)
res2 <- aggvar(hyperLOPIT2015ms3r1psm, groupBy, fun = mean)
par(mfrow = c(1, 3))
plot(res1, log = "y", main = "Single outliers (max)")
plot(res2, log = "y", main = "Overall inconsistency (mean)")
plot(res1[, "agg_dist"], res2[, "agg_dist"],
xlab = "max", ylab = "mean")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.