orderGoAnnotations(object, fcol = "GOAnnotations", k = 1:5, n = 5, p = 1/3, verbose = TRUE, seed)
MSnSet
.GOAnnotations
.k = 1:5
k
testedlogical
indicating if a progress bar should
be displayed. Default is TRUE
.MSnSet
containing the newly ordered
fcol
matrix.
For each protein set i.e. proteins that have been labelled
with a specified term/information criteria, we find the best
k
cluster components for the set (the default is to
testk = 1:5
) according to the minimum mean normalised
pairwise Euclidean distance over all component clusters.
(Note: when testing k
if any components are found to
have less than n
proteins these components are not
included and k
is reduced by 1).
Each component cluster is normalised by N^p
(where
N
is the total number of proteins per component,
and p
is the power). Hueristally, p = 1/3
and normalising by N^1/3
has been found the optimum
normalisation factor.
Candidates in the matrix are ordered according to lowest mean normalised pairwise Euclidean distance as we expect high density, tight clusters to have the smallest mean normalised distance.
This function is a wrapper for running clustDist
,
getNormDist
, see the "Annotating spatial proteomics data"
vignette for more details.
addGoAnnotations
and example therein.