向量化包含循环和if子句的搜索函数

Question

我给了两个非常大的数据集,我一直在尝试构建一个函数,该函数可以从一个集合中找到某个坐标,该坐标尊重关于其他数据集的if子句.我的问题是我写的函数非常慢,虽然我一直在以某种方式阅读类似问题的答案,但我还是没有成功.
所以如果给我:

>head(CTSS)    
    V1     V2     V3
1 chr1 564563 564598 
2 chr1 564620 564649
3 chr1 565369 565404
4 chr1 565463 565541
5 chr1 565653 565697
6 chr1 565861 565922

和

> head(href)
   chr      region    start      end strand nu   gene_id transcript_id
1 chr1 start_codon 67000042 67000044      +  . NM_032291     NM_032291
2 chr1         CDS 67000042 67000051      +  0 NM_032291     NM_032291
3 chr1        exon 66999825 67000051      +  . NM_032291     NM_032291
4 chr1         CDS 67091530 67091593      +  2 NM_032291     NM_032291
5 chr1        exon 67091530 67091593      +  . NM_032291     NM_032291
6 chr1         CDS 67098753 67098777      +  1 NM_032291     NM_032291

对于在每个值起始列从HREF数据集我想找到的CTSS数据的第三列的前两个值设置小于或大于等于它,并把它放在一个新的数据帧.
我写的循环:

y <- CTSS[order(-CTSS$V3), ]     
find_CTSS <- function(x, y) {
    n <- length(x$start)
    foo <- data.frame(matrix(0, n, 6))
    for (i in 1:n)
    {
        a <- which(y$V3 <= x$start[i])
        foo[i, ] = c(x$start[i], x$stop[i], y$V2[a[1]], y$V3[a[1]] , y$V2[a[2]], y$V3[a[2]])
    }

print(foo)

}

Answer 1

您提供的数据很少(但请参见此处),因此对您的解决方案进行基准测试有点困难.查看以下解决方案是否满足您的需求.

#make some fake data
href <- data.frame(start = runif(10), stop = runif(10), other_col = sample(letters, 10))
CTSS <- data.frame(col1 = runif(100), col2 = runif(100))

# for each row in href (but extract only stop and start columns)
result <- apply(X = href[, c("start", "stop")], MARGIN = 1, FUN = function(x, ctss) {
            criterion <- x["start"] #make a criterion
            #see which values are smaller or equal to this criterion (and sort them)
            extracted <- sort(ctss[ctss$col2 <= criterion, "col2"])
            #extract last and one to last value
            get.values <- extracted[c(length(extracted) - 1, length(extracted))] 
            #put values in data frame
            out <- as.data.frame(matrix(get.values, ncol = 2)) 
            return(out)
        }, ctss = CTSS)

#pancake a list into a data.frame
result <- do.call("rbind", result)