R NMF package: Как извлечь образцы классификации?

Question

В R-пакете NMF можно использовать консенсус() для визуализации выходов. Графики показывают, какие образцы принадлежат к кластерам на «консенсусной» дорожке.

Я хотел бы извлечь этот пример классификации таким образом, что я получаю кадр данных, как это:

Sample Cluster 
S1  1 
S2  1 
S3  2 
S4  1 
.   . 
.   . 
S100  2 

В пакете ConsensusClusterPlus это легко. Вы просто вытаскиваете результаты $ contestClass. Я не могу найти аналогичное решение для NMF-пакета. Я попытался посмотреть исходные данные графика, но он слишком запутан, чтобы извлечь какой-либо смысл.

Вот иллюстрация проблемы: мне нужно выяснить, какой «статус» находится в пределах «консенсуса».

Answer 1

Прогулка все дерево и рассчитывать?

> v <- syntheticNMF(20, 3, 10) 

> xx<-consensusmap(x) 

> str(xx) 
List of 4 
$ Rowv : ..--[dendrogram w/ 2 branches and 10 members at h = 1, midpoint = 5.97, value = 3.4] 
    .. |--[dendrogram w/ 2 branches and 7 members at h = 1, midpoint = 3.69, value = 2.5] 
    .. | |--[dendrogram w/ 2 branches and 4 members at h = 0, midpoint = 2.12, value = 1.6] 
    .. | | |--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 1.25, value = 1.2] 
    .. | | | |--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.8] 
    .. | | | | |--leaf "2" (value.2 = 0.4) 
    .. | | | | `--leaf "1" (value.1 = 0.4) 
    .. | | | `--leaf "3" (value.3 = 0.4) 
    .. | | `--leaf "4" (value.4 = 0.4) 
    .. | `--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 1.25, value = 0.9] 
    .. |  |--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.6] 
    .. |  | |--leaf "6" (value.6 = 0.3) 
    .. |  | `--leaf "5" (value.5 = 0.3) 
    .. |  `--leaf "7" (value.7 = 0.3) 
    .. `--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 1.25, value = 0.9] 
    ..  |--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.6] 
    ..  | |--leaf "9" (value.9 = 0.3) 
    ..  | `--leaf "8" (value.8 = 0.3) 
    ..  `--leaf "10" (value.10 = 0.3) 
    $ rowInd: int [1:10] 2 1 3 4 6 5 7 9 8 10 
    $ Colv : ..--[dendrogram w/ 2 branches and 10 members at h = 1, midpoint = 3.03, value = 3.4] 
    .. |--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 0.75, value = 0.9] 
    .. | |--leaf "10" (value.10 = 0.3) 
    .. | `--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.6] 
    .. |  |--leaf "8" (value.8 = 0.3) 
    .. |  `--leaf "9" (value.9 = 0.3) 
    .. `--[dendrogram w/ 2 branches and 7 members at h = 1, midpoint = 2.31, value = 2.5] 
    ..  |--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 0.75, value = 0.9] 
    ..  | |--leaf "7" (value.7 = 0.3) 
    ..  | `--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.6] 
    ..  |  |--leaf "5" (value.5 = 0.3) 
    ..  |  `--leaf "6" (value.6 = 0.3) 
    ..  `--[dendrogram w/ 2 branches and 4 members at h = 0, midpoint = 0.875, value = 1.6] 
    ..  |--leaf "4" (value.4 = 0.4) 
    ..  `--[dendrogram w/ 2 branches and 3 members at h = 0, midpoint = 0.75, value = 1.2] 
    ..   |--leaf "3" (value.3 = 0.4) 
    ..   `--[dendrogram w/ 2 branches and 2 members at h = 0, midpoint = 0.5, value = 0.8] 
    ..    |--leaf "1" (value.1 = 0.4) 
    ..    `--leaf "2" (value.2 = 0.4) 
$ colInd: int [1:10] 10 8 9 7 5 6 4 3 1 2 


> lapply(cut(xx$Rowv,0.5)$lower, function(l) rapply(l, function(i) i)) 
[[1]] 
[1] 2 1 3 4 

[[2]] 
[1] 6 5 7 

[[3]] 
[1] 9 8 10