R-从基于第二个数据帧的数据帧中删除特定的数字范围，并重塑所有内容

Question

我有一个数据帧("引用"(，包含3条人类染色体的基因组位置("起始"one_answers"结束"列(("eqnames"列(。我需要基于第二个数据帧("黑名单"(从每个染色体中删除特定的范围，并重塑原始数据帧以从每个染色体排除这些范围。我试图将这些数据帧作为一个GRanges对象(GenomicRanges库(读取，但我没有找到任何函数来执行此特定操作，所以作为一个数据帧可能会更容易？

reference <- data.frame(seqnames = c('chr1','chr2','chr3'),
start = c(1,1,1),
end = c(248956422, 242193529, 198295559)
)
reference 
seqnames    start   end
<chr>   <dbl>   <dbl>
chr1    1   248956422
chr2    1   242193529
chr3    1   198295559
blacklist <- data.frame(seqnames = c('chr1','chr1','chr1','chr2','chr2','chr3','chr3'),
start = c(628903, 5850087, 8909610, 10, 23123, 163123, 3163123),
end = c(635104, 5850571, 8910014, 9312, 27120, 193120, 3963122)
)
blacklist 
seqnames    start   end
<chr>   <dbl>   <dbl>
chr1    628903  635104
chr1    5850087 5850571
chr1    8909610 8910014
chr2    10  9312
chr2    23123   27120
chr3    163123  193120
chr3    3163123 3963122

所需输出(新数据帧"reference_new"(：

reference_new <- data.frame(seqnames = c('chr1','chr1','chr1','chr1','chr2', 'chr2', 'chr2', 'chr3', 'chr3', 'chr3' ),
start = c(1, 635105, 5850572,8910015, 1, 9313,27121, 1,193121,3963123 ),
end = c(628902, 5850086,8909609, 248956422, 9, 23122,242193529, 163122,3163122, 198295559)
)           
reference_new
seqnames    start   end
<chr>   <dbl>   <dbl>
chr1    1   628902
chr1    635105  5850086
chr1    5850572 8909609
chr1    8910015 248956422
chr2    1   9
chr2    9313    23122
chr2    27121   242193529
chr3    1   163122
chr3    193121  3163122
chr3    3963123 198295559

Answer 1

这感觉很笨拙，但适用于示例数据。我没有检查参考范围之外的黑名单值，所以我怀疑这会造成问题，可能值得更多的检查/不同的方法。

library(tidyverse)
conv_shape <- function(df, rev = 1) {
df%>%
pivot_longer(-seqnames) %>%
mutate(value = value + case_when(rev == -1 & name == "start" ~ -1,
rev == -1 & name == "end" ~ 1,
TRUE ~ 0),
active = if_else(name == "start", 1, -1) * rev)
}
bind_rows(.id = "src",
ref = reference %>% conv_shape,
blacklist = blacklist %>% conv_shape(-1)
) %>%
arrange(seqnames, value) %>%
group_by(seqnames) %>%
mutate(inrng = cumsum(active),
status = if_else(inrng == 1, "start", "end"),
grp = cumsum(inrng - lag(inrng, default = 0) == 1)) %>%
ungroup() %>%
select(seqnames, value, status, grp) %>%
pivot_wider(names_from = status, values_from = value)

结果

# A tibble: 10 × 4
seqnames   grp   start       end
<chr>    <int>   <dbl>     <dbl>
1 chr1         1       1    628902
2 chr1         2  635105   5850086
3 chr1         3 5850572   8909609
4 chr1         4 8910015 248956422
5 chr2         1       1         9
6 chr2         2    9313     23122
7 chr2         3   27121 242193529
8 chr3         1       1    163122
9 chr3         2  193121   3163122
10 chr3         3 3963123 198295559