删除R中重叠的ATAC序列峰值

Question

我有一份ATAC序列窄峰的档案。与PEPATAC流水线类似，这里的算法是:首先，保留最重要的峰值，并删除与该显著峰值直接重叠的任何峰值。然后，此过程迭代到下一个最重要的峰值，依此类推，直到由于与更重要的峰值直接重叠而保留或移除了所有峰值。

以下是我的数据示例

data <- structure(list(V1 = c("chr3", "chrUn_KI270467v1", "chr8", "chrUn_KI270467v1", 
"chr21", "chr7"), V2 = c(93470281L, 1668L, 109333171L, 1668L, 
14382415L, 12686167L), V3 = c(93470873L, 3946L, 109335050L, 3946L, 
14384230L, 12688127L), V4 = c("Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_60893", 
"Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_97388b", "Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_92241d", 
"Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_97388c", "Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_55158c", 
"Bcell-BM4983-150120-RepA.pe.q10.sort.rmdup_peak_83188b"), V5 = c(91371L, 
24480L, 19002L, 17131L, 17084L, 16639L), V6 = c(".", ".", ".", 
".", ".", "."), V7 = c(726.76721, 240.65007, 195.49055, 179.63454, 
179.23312, 175.41965), V8 = c(9144.74609, 2454.88721, 1906.9408, 
1719.66797, 1714.96497, 1670.38489), V9 = c(9137.11816, 2448.07471, 
1900.24915, 1713.15186, 1708.45618, 1663.93958), V10 = c(272L, 
666L, 1082L, 1445L, 898L, 525L)), row.names = c(88715L, 141209L, 
133771L, 141210L, 80584L, 120831L), class = "data.frame")

我根据它们的重要性对峰值进行了排序。到目前为止，我写了这段代码

 for ( i in 1:nrow(B1.1)){
      sub<-as_granges(B1.1[i , ], seqnames=1, start=2 , end=3)
      que<- as_granges(B1.1 , seqnames=V1 , start=V2 , end=V3)
      overlaps<-which(overlapsAny( que, sub))
      overlaps<-overlaps[overlaps!=i ]
      B1.1<-B1.1[ ! seq(from=1 , to=nrow(B1.1), by=1)%in%overlaps, ]
      overlaps<-c()
    }

显然，这段代码效率不是很高，而且需要花费大量时间。

非常感谢您的建议

Answer 1

您为间隔定义了组，并对您的GRanges对象进行了重复数据删除，因为我不能用您的数据显示它，下面是一个根据p值排序的示例数据：

library(GenomicRanges)

gr = GRanges(seqnames=1,
IRanges(start=c(1,1,1,1,5,5),end=c(3,3,2,2,8,9)),
p=sort(runif(6,0,0.1)))

使用reduce定义组，首先创建一个包含所有重叠的宽间隔：

rgr = reduce(gr)

rgr

GRanges object with 2 ranges and 0 metadata columns:
      seqnames    ranges strand
         <Rle> <IRanges>  <Rle>
  [1]        1       1-3      *
  [2]        1       5-9      *
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths

现在使用findOverlaps将各个范围分配给组

gr$group = subjectHits(findOverlaps(gr,rgr))

对此进行重复数据删除：

gr[!duplicated(gr$group)]

GRanges object with 2 ranges and 2 metadata columns:
      seqnames    ranges strand |                  p     group
         <Rle> <IRanges>  <Rle> |          <numeric> <integer>
  [1]        1       1-3      * | 0.0276333122281358         1
  [2]        1       5-8      * | 0.0465503185754642         2
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths

另一种方法是使用while循环：

findNonOvlp = function(g){

   idx = seq_along(g)
   keep = c()
   while(length(idx)>0){
      top_g = idx[1]
      rmv = idx[countOverlaps(g[idx],g[top_g])>0]
      idx = setdiff(idx,rmv)
      keep = c(keep,top_g)
   }
   g[keep]
 }   

测试：

findNonOvlp(gr)

GRanges object with 2 ranges and 1 metadata column:
      seqnames    ranges strand |                   p
         <Rle> <IRanges>  <Rle> |           <numeric>
  [1]        1       1-3      * | 0.00038885809481144
  [2]        1       5-8      * |   0.058683192031458
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths

再举一个例子：

r = GRanges(seqnames=c("chr1", "chr1", "chr1"), IRanges(start=c(100,140,180),end=c(150,200, 200) ) )

findNonOvlp(r)

GRanges object with 2 ranges and 0 metadata columns:
      seqnames    ranges strand
         <Rle> <IRanges>  <Rle>
  [1]     chr1   100-150      *
  [2]     chr1   180-200      *
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths