当我在 RI 中计算自举树时，会得到与使用 PAST 时不同的值（http://folk.uio.no/ohammer/past/）。如何使两个程序的输出匹配？
这是我在 R 中所做的事情（数据如下）：
library("ape")
library("phytools")
library("phangorn")
library("cluster")
# compute neighbour-joined tree
f <- function(xx) nj(daisy(xx))
nj_tree <- f(tab)
nj_tree_root <- root(nj_tree, 1, r = TRUE)
## bootstrap
# bootstrap values do not match PAST output - why is that?
nj_tree_root_boot <- boot.phylo(nj_tree, FUN = f, tab, rooted = TRUE)
# Are bootstrap values stable?
for (i in 1:10){
print(boot.phylo(nj_tree, FUN = f, tab, rooted = TRUE, quiet = TRUE))
}
# yes, they seem ok
# plot tree with bootstrap values
plot(nj_tree_root, use.edge.length = FALSE)
nodelabels(nj_tree_root_boot, adj = c(1.2, 1.2), frame = "none")
引导程序的典型输出是[1] 100 6 39 27 23 57 53 75 71，这里是情节（远 LHS 值应该是 100，它以某种方式被裁剪）：
我转换数据以将其发送到 PAST，如下所示：
tab1 <- t(apply(tab, 1, as.numeric))
write.table(tab1, "tab.txt")
在过去，我打开 tab.txt 文件，使用外群执行多元 -> 集群 -> 使用欧几里得和 100 次引导复制的邻居加入。从过去我得到这个情节：
而且价值观相差很大。我需要用 R 做什么才能使输出与过去的输出匹配？过去是错的吗？
数据：
tab <- structure(list(X1 = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L), .Label = c("0", "1"), class = "factor"), X2 = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("0", "1"), class = "factor"),
X3 = structure(c(1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L,
2L), .Label = c("0", "1"), class = "factor"), X4 = structure(c(2L,
2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L), .Label = c("0",
"1"), class = "factor"), X5 = structure(c(1L, 1L, 1L, 1L,
2L, 2L, 1L, 2L, 1L, 2L, 1L), .Label = c("0", "1"), class = "factor"),
X6 = structure(c(1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L,
2L), .Label = c("0", "1"), class = "factor"), X7 = structure(c(1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("0",
"1"), class = "factor"), X8 = structure(c(2L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 1L, 2L, 2L), .Label = c("0", "1"), class = "factor"),
X9 = structure(c(1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L,
1L), .Label = c("0", "1"), class = "factor"), X10 = structure(c(1L,
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L), .Label = c("0",
"1"), class = "factor"), X11 = structure(c(1L, 2L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 2L), .Label = c("0", "1"), class = "factor"),
X12 = structure(c(2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = c("0", "1"), class = "factor"), X13 = structure(c(2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0",
"1"), class = "factor"), X14 = structure(c(2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1"), class = "factor"),
X15 = structure(c(2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L), .Label = c("0", "1"), class = "factor"), X16 = structure(c(2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L), .Label = c("0",
"1"), class = "factor"), X17 = structure(c(2L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 1L, 2L), .Label = c("0", "1"), class = "factor"),
X18 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L,
1L), .Label = c("0", "1"), class = "factor"), X19 = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L), .Label = c("0",
"1"), class = "factor"), X20 = structure(c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L), .Label = c("0", "1"), class = "factor"),
X21 = structure(c(1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = c("0", "1"), class = "factor"), X22 = structure(c(2L,
2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L), .Label = c("0",
"1"), class = "factor"), X23 = structure(c(1L, 1L, 2L, 1L,
1L, 1L, 1L, 2L, 1L, 2L, 2L), .Label = c("0", "1"), class = "factor"),
X24 = structure(c(1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L,
2L), .Label = c("0", "1"), class = "factor"), X25 = structure(c(1L,
1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L), .Label = c("0",
"1"), class = "factor"), X26 = structure(c(1L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 1L, 1L, 1L), .Label = c("0", "1"), class = "factor")), .Names = c("X1",
"X2", "X3", "X4", "X5", "X6", "X7", "X8", "X9", "X10", "X11",
"X12", "X13", "X14", "X15", "X16", "X17", "X18", "X19", "X20",
"X21", "X22", "X23", "X24", "X25", "X26"), row.names = c("a",
"b", "c", "d", "e", "f", "g", "h", "i", "j", "k"), class = "data.frame")
