Description Usage Arguments Value Methods (by class) See Also Examples
This method takes a similarity matrix based on all genes in the pangenome,
converts it to a graph representation and uses one of igraphs community
detection algorithms to split all genes into groups. Within the FindMyFriends
framework the similarity matrix would usually come from
kmerSimilarity
, but it can just as well be defined in other
ways e.g. be blast derived.
1 2 3 4 | graphGrouping(object, ...)
## S4 method for signature 'pgVirtual'
graphGrouping(object, similarity, algorithm, ...)
|
object |
A pgVirtual subclass |
... |
parameters to be passed on to the community detection algorithm |
similarity |
A similarity matrix with rows and columns corresponding to the genes in the pangenome. |
algorithm |
A string naming the algorithm. See
|
An object of the same class as 'object'.
pgVirtual
: graph grouping for all pgVirtual subclasses
Other grouping algorithms: cdhitGrouping
,
gpcGrouping
, manualGrouping
1 2 3 4 5 6 7 8 9 10 11 | testPG <- .loadPgExample()
# Too heavy to include
## Not run:
# Generate similarity matrix
simMat <- kmerSimilarity(testPG, lowerLimit=0.75)
# Group genes
testPG <- graphGrouping(testPG, simMat)
## End(Not run)
|
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