我有一个这样的数据框(df2):
locus transect fq d
Locus_1 A 0.000 20
Locus_1 A 0.000 35
Locus_1 A 0.000 50
Locus_2 A 0.200 20
Locus_2 A 0.083 35
Locus_2 A 0.125 50
Locus_3 A 0.134 20
Locus_3 A 0.208 35
Locus_3 A 0.218 50
Locus_4 A 0.000 20
Locus_4 A 0.000 35
Locus_4 A 0.000 50
Locus_5 A 0.100 20
Locus_5 A 0.000 35
Locus_5 A 0.038 50 ...
基本上,每个轨迹在距中心不同距离的样带上采样 3 次。有数千个位点。从这个数据集中,我计算了频率和距离之间的相关性。
接下来的步骤是:
- 随机化每个基因座的位置(因此,前三行,第二组三行等),计算新的相关性。基本上,我想在每个基因座之间打乱 d 值(20-35-50)。离子
- 这样做 1000 次
- 保存每个重复的结果
我正在尝试主要使用Plyr
and dplyr
。
这是我想出的代码:
df3 <- group_by(df2, transect, locus) #setting up groups to which apply functions
data <- replicate(1000, {
test <- sample_n(df3, 3, replace=F) #shuffle by group
Rho <- ddply(test, .(transect, locus), summarise, corr= cor(fq, d, method = "spearman")) #calculate correlation
Rho[is.na(Rho)] <- 0 #replacing missing values with zero
Rho_mean_bylocus <- ddply(Rho, .(locus), summarise, mean=mean(corr)) #average correlation over transect
}, simplify = TRUE)
结果如下:
[,1] [,2] [,3] [,4]
locus factor,978 factor,978 factor,978 factor,978
mean Numeric,978 Numeric,978 Numeric,978 Numeric,978
[,5] [,6] [,7] [,8]
locus factor,978 factor,978 factor,978 factor,978
mean Numeric,978 Numeric,978 Numeric,978 Numeric,978
[,9] [,10]
locus factor,978 factor,978
mean Numeric,978 Numeric,978
(我有 978 个位点)。
我试图嵌入replicate()
一个函数
rand.rho <- function(x) { #I have tried also without using a function, but still does not work
data <- replicate(1000, {
test <- sample_n(df3, 3, replace=F) #shuffle
Rho <- ddply(test, .(transect, locus), summarise, corr= cor(fq, d, method = "spearman")) #calculate correlation
Rho[is.na(Rho)] <- 0 #replacing missing values with zero
Rho_mean_bylocus <- ddply(Rho, .(locus), summarise, mean=mean(corr)) #average correlation over transect
}, simplify = TRUE)
df4 <- rand.rho(df3)
但我收到一个错误:
Error in list_to_dataframe(res, attr(.data, "split_labels"), .id, id_as_factor) :
Results must be all atomic, or all data frames
In addition: There were 50 or more warnings (use warnings() to see the first 50)
我不知所措。
我已经在这里寻找其他答案并尝试实施该建议,但仍然无法正常工作。
有什么建议吗?