0

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Plyrand 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?

4

0 回答 0