使用data.table为组的每个元素创建"索引"

Question

我的数据按V6中的ID分组,按位置排序(V1:V3):

dt
      V1      V2      V3 V4 V5                 V6
 1: chr1 3054233 3054733  .  + ENSMUSG00000090025
 2: chr1 3102016 3102125  .  + ENSMUSG00000064842
 3: chr1 3205901 3207317  .  - ENSMUSG00000051951
 4: chr1 3206523 3207317  .  - ENSMUSG00000051951
 5: chr1 3213439 3215632  .  - ENSMUSG00000051951
 6: chr1 3213609 3216344  .  - ENSMUSG00000051951
 7: chr1 3214482 3216968  .  - ENSMUSG00000051951
 8: chr1 3421702 3421901  .  - ENSMUSG00000051951
 9: chr1 3466587 3466687  .  + ENSMUSG00000089699
10: chr1 3513405 3513553  .  + ENSMUSG00000089699

我想要做的是添加一个带位置索引的额外列,也就是说,每个组在V6中第一个元素是"1",第二个元素是"2",依此类推.我可以使用ddply和自定义函数实现:

rankExons <- function(x){
   if(unique(x$V5) == "+"){ 
         x$index <- seq_len(nrow(x))}
   else{
         x$index <- rev(seq_len(nrow(x)))}
   x
}

indexed <- ddply(dt, .(V6), rankExons)
indexed
     V1      V2      V3 V4 V5                 V6 index
1  chr1 3205901 3207317  .  - ENSMUSG00000051951     6
2  chr1 3206523 3207317  .  - ENSMUSG00000051951     5
3  chr1 3213439 3215632  .  - ENSMUSG00000051951     4
4  chr1 3213609 3216344  .  - ENSMUSG00000051951     3
5  chr1 3214482 3216968  .  - ENSMUSG00000051951     2
6  chr1 3421702 3421901  .  - ENSMUSG00000051951     1
7  chr1 3102016 3102125  .  + ENSMUSG00000064842     1
8  chr1 3466587 3466687  .  + ENSMUSG00000089699     1
9  chr1 3513405 3513553  .  + ENSMUSG00000089699     2
10 chr1 3054233 3054733  .  + ENSMUSG00000090025     1

不幸的是,它在整个数据集(~620k行)上非常慢,并且当使用并行时它会崩溃和烧伤:

library(doMC)
registerDoMC(cores=6)
indexed <- ddply(dt, .(V6), rankExons, .parallel=TRUE)
Error: serialization is too large to store in a raw vector
Error: serialization is too large to store in a raw vector
Error: serialization is too large to store in a raw vector
Error: serialization is too large to store in a raw vector
Error: serialization is too large to store in a raw vector
Error: serialization is too large to store in a raw vector
Warning message:
In mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,  :
  all scheduled cores encountered errors in user code

所以,我去了data.table但是无法让它工作.这是我尝试过的:

setkey(dt, "V6")

dt[,index:=rankExons(dt), by=V6]
dt[,rankExons(.sd), by=V6, .SDcols=c("V5, V6")]

两者都失败了.如何使用data.table重新创建ddply？

dput(dt)
structure(list(V1 = c("chr1", "chr1", "chr1", "chr1", "chr1", 
"chr1", "chr1", "chr1", "chr1", "chr1"), V2 = c(3054233L, 3102016L, 
3205901L, 3206523L, 3213439L, 3213609L, 3214482L, 3421702L, 3466587L, 
3513405L), V3 = c(3054733L, 3102125L, 3207317L, 3207317L, 3215632L, 
3216344L, 3216968L, 3421901L, 3466687L, 3513553L), V4 = c(".", 
".", ".", ".", ".", ".", ".", ".", ".", "."), V5 = c("+", "+", 
"-", "-", "-", "-", "-", "-", "+", "+"), V6 = c("ENSMUSG00000090025", 
"ENSMUSG00000064842", "ENSMUSG00000051951", "ENSMUSG00000051951", 
"ENSMUSG00000051951", "ENSMUSG00000051951", "ENSMUSG00000051951", 
"ENSMUSG00000051951", "ENSMUSG00000089699", "ENSMUSG00000089699"
)), .Names = c("V1", "V2", "V3", "V4", "V5", "V6"), class = c("data.table", 
"data.frame"), row.names = c(NA, -10L), .internal.selfref = <pointer: 0x1de6a88>)

Answer 1

作为生物信息学家,我经常遇到这种操作.而这正是我喜欢data.table的参照修改行的子集的功能!

我这样做:

dt[V5 == "+", index := 1:.N, by=V6]
dt[V5 == "-", index := .N:1, by=V6]

无需任何功能.这有点更有利,因为它避免了必须为每个组检查== "+"或"-"一次!相反,您可以先使用一次对所有组进行子集化,然后进行分组,然后仅修改这些行!+ V6

同样,你再次这样做"-".希望有所帮助.

注意:.N是一个特殊变量,包含每组的观察数.