从包含键值对的字符串有效地创建数据帧

Question

我想问一下R中特定编码问题的效率建议.我有一个以下样式的字符串向量:

[1] "HGVSc=ENST00000495576.1:n.820-1G>A;INTRON=1/1;CANONICAL=YES"
[2] "DISTANCE=2179"                                              
[3] "HGVSc=ENST00000466430.1:n.911C>T;EXON=4/4;CANONICAL=YES"    
[4] "DISTANCE=27;CANONICAL=YES;common"

在向量的每个元素中,单个条目用a ;和MOST 分隔,单个条目具有格式KEY=VALUE.但是,也有一些条目只有格式KEY(参见[4]中的"common").在此示例中,有15个不同的键,并不是每个键都出现在向量的每个元素中.15个不同的键是:

names <- c('ENSP','HGVS','DOMAINS','EXON','INTRON', 'HGVSp', 'HGVSc','CANONICAL','GMAF','DISTANCE', 'HGNC', 'CCDS', 'SIFT', 'PolyPhen', 'common')

从这个向量我想创建一个如下所示的数据帧:

ENSP HGVS DOMAINS EXON INTRON HGVSp                        HGVSc CANONICAL
1    -    -       -    -    1/1     - ENST00000495576.1:n.820-1G>A       YES
2    -    -       -    -      -     -                            -         -
3    -    -       -  4/4      -     -   ENST00000466430.1:n.911C>T       YES
4    -    -       -    -      -     -                            -       YES
GMAF DISTANCE HGNC CCDS SIFT PolyPhen common
1    -        -    -    -    -        -      -
2    -     2179    -    -    -        -      -
3    -        -    -    -    -        -      -
4    -       27    -    -    -        -    YES

我写了这个函数来解决问题:

unlist.info <- function(names, column){
  info.mat <- matrix(rep('-', length(column)*length(names)), nrow=length(column), ncol=length(names), dimnames=list(c(), names))
  info.mat <- as.data.frame(info.mat, stringsAsFactors=F)

  for (i in 1:length(column)){
    info <- unlist(strsplit(column[i], "\\;"))
    for (e in info){
      e <- unlist(strsplit(e, "\\="))
      j <- which(names == e[1])
      if (length(e) > 1){
        # KEY=VALUE. The value might contain a = as well
        value <- paste(e[2:length(e)], collapse='=')
        info.mat[i,j] <- value
      }else{
        # only KEY
        info.mat[i,j] <- 'YES'
      }
    }
  }
  return(info.mat)
}

然后我打电话给:

mat <- unlist.info(names, vector)

尽管这很有效,但它确实很慢.此外,我正在处理超过100,000条目的向量.现在我意识到循环在R中是不优雅和低效的,我熟悉将函数应用于数据帧的概念.但是,由于向量的每个条目都包含不同的子集KEY=VALUE或KEY条目,因此无法提供更高效的函数.

Answer 1

干得好:

重新创建数据:

x <- c(
  "HGVSc=ENST00000495576.1:n.820-1G>A;INTRON=1//1;CANONICAL=YES",
  "DISTANCE=2179",
  "HGVSc=ENST00000466430.1:n.911C>T;EXON=4//4;CANONICAL=YES",
  "DISTANCE=27;CANONICAL=YES;common"
)

使用所需名称创建命名向量.这用于以后快速查找:

names <- setNames(1:15, c('ENSP','HGVS','DOMAINS','EXON','INTRON', 'HGVSp', 'HGVSc','CANONICAL','GMAF','DISTANCE', 'HGNC', 'CCDS', 'SIFT', 'PolyPhen', 'common'))

创建一个辅助函数,将每个变量分配给矩阵中的正确位置.然后使用lapply和strsplit:

assign <- function(x, names){
  xx <- sapply(x, function(i)if(length(i)==2L) i else c(i, "YES"))
  z <- rep(NA, length(names))
  z[names[xx[1, ]]] <- xx[2, ]
  z
}

sx <- lapply(strsplit(x, ";"), strsplit, "=")
ret <- t(sapply(sx, assign, names))
colnames(ret) <- names(names)
ret

结果:

     ENSP HGVS DOMAINS EXON   INTRON HGVSp HGVSc                          CANONICAL GMAF DISTANCE HGNC
[1,] NA   NA   NA      NA     "1//1" NA    "ENST00000495576.1:n.820-1G>A" "YES"     NA   NA       NA  
[2,] NA   NA   NA      NA     NA     NA    NA                             NA        NA   "2179"   NA  
[3,] NA   NA   NA      "4//4" NA     NA    "ENST00000466430.1:n.911C>T"   "YES"     NA   NA       NA  
[4,] NA   NA   NA      NA     NA     NA    NA                             "YES"     NA   "27"     NA  
     CCDS SIFT PolyPhen common
[1,] NA   NA   NA       NA    
[2,] NA   NA   NA       NA    
[3,] NA   NA   NA       NA    
[4,] NA   NA   NA       "YES"