Description Usage Arguments Details Value Author(s) Examples
Analyze a set of phylogenetic trees and attempt to identify trees which are significantly discordant with other trees in the sample (outlier trees).
1 2 |
trees |
multiPhylo object |
k |
IQR multiplier for outlier detection |
distance |
Select "geodesic" or "dissimilarity" distance calculation method |
outgroup |
if a character, reroot all trees with this species as outgroup. The geodesic distance method requires rooted trees. |
topo.only |
set all branch lengths to 1 before analyzing? |
bw |
see Details |
greedy |
greedy outlier detection? |
... |
additional arguments for distance calculation function, see details |
If bw is a single number, it will be used as a single constant bandwidth. It can also be a vector, in which case it will be used as variable bandwidths for each tree, repectively. Finally, if it is a list (default), the list will be passed as arguments to the bw.nn adaptive bandwith function.
... Is passed to either distory::dist.multiPhylo
or
dist.diss
, as appropriate. See the help for these functions
for more details.
a kdetrees object; list(density,outliers)
Grady Weyenberg
1 2 3 4 5 | kdeobj <- kdetrees(apicomplexa)
print(kdeobj)
kdeobj$outliers
kdetrees(apicomplexa, k=2.0, distance="dissimilarity",topo.only=FALSE)
|
Call: kdetrees(trees = apicomplexa)
Density estimates:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.9963 65.8651 82.6407 77.2972 94.4934 114.5458
Cutoff: 22.92261
Outliers detected:
[1] 488.tre 497.tre 515.tre 546.tre 547.tre 641.tre 660.tre 662.tre 728.tre
[10] 747.tre 773.tre 780.tre
12 phylogenetic trees
Call: kdetrees(trees = apicomplexa, k = 2, distance = "dissimilarity",
topo.only = FALSE)
Density estimates:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.3732 19.5469 24.4732 23.1004 29.0376 35.2785
Cutoff: 0.5653973
Outliers detected:
[1] 497.tre 515.tre 546.tre 547.tre 662.tre 728.tre 747.tre 773.tre 780.tre
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