Pair together two ranges objects
pair_overlaps(x, y, maxgap, minoverlap, suffix)
pair_nearest(x, y, suffix)
pair_precede(x, y, suffix)
pair_follow(x, y, suffix)Ranges objects to pair together.
The maximimum gap between intervals as an integer greater than or equal to negative one. The minimum amount of overlap between intervals as an integer greater than zero, accounting for the maximum gap.
A character vector of length two used to identify metadata columns coming from x and y.
a DataFrame with two ranges columns and the corresponding metadata columns.
These functions return a DataFrame object, and is one way of representing paired alignments with plyranges.
[join_nearest()][join_overlap_inner()][join_precede()][join_follow()]
query <- data.frame(start = c(5,10, 15,20), width = 5, gc = runif(4)) %>%
as_iranges()
subject <- data.frame(start = 2:6, width = 3:7, label = letters[1:5]) %>%
as_iranges()
pair_overlaps(query, subject)
#> DataFrame with 6 rows and 4 columns
#> ranges.x ranges.y gc label
#> <IRanges> <IRanges> <numeric> <character>
#> 1 5-9 3-6 0.836571 b
#> 2 5-9 4-8 0.836571 c
#> 3 5-9 5-10 0.836571 d
#> 4 5-9 6-12 0.836571 e
#> 5 10-14 5-10 0.806867 d
#> 6 10-14 6-12 0.806867 e
pair_overlaps(query, subject, minoverlap = 5)
#> DataFrame with 1 row and 4 columns
#> ranges.x ranges.y gc label
#> <IRanges> <IRanges> <numeric> <character>
#> 1 5-9 5-10 0.836571 d
pair_nearest(query, subject)
#> DataFrame with 4 rows and 4 columns
#> ranges.x ranges.y gc label
#> <IRanges> <IRanges> <numeric> <character>
#> 1 5-9 6-12 0.8365715 e
#> 2 10-14 6-12 0.8068667 e
#> 3 15-19 6-12 0.0809326 e
#> 4 20-24 6-12 0.2389093 e
query <- data.frame(seqnames = "chr1",
start = c(11,101),
end = c(21, 200),
name = c("a1", "a2"),
strand = c("+", "-"),
score = c(1,2)) %>%
as_granges()
subject <- data.frame(seqnames = "chr1",
strand = c("+", "-", "+", "-"),
start = c(21,91,101,201),
end = c(30,101,110,210),
name = paste0("b", 1:4),
score = 1:4) %>%
as_granges()
# ignores strandedness
pair_overlaps(query, subject, suffix = c(".query", ".subject"))
#> DataFrame with 3 rows and 6 columns
#> granges.query granges.subject name.query score.query name.subject
#> <GRanges> <GRanges> <character> <numeric> <character>
#> 1 chr1:11-21:+ chr1:21-30:+ a1 1 b1
#> 2 chr1:101-200:- chr1:91-101:- a2 2 b2
#> 3 chr1:101-200:- chr1:101-110:+ a2 2 b3
#> score.subject
#> <integer>
#> 1 1
#> 2 2
#> 3 3
pair_follow(query, subject, suffix = c(".query", ".subject"))
#> DataFrame with 1 row and 6 columns
#> granges.query granges.subject name.query score.query name.subject
#> <GRanges> <GRanges> <character> <numeric> <character>
#> 1 chr1:101-200:- chr1:21-30:+ a2 2 b1
#> score.subject
#> <integer>
#> 1 1
pair_precede(query, subject, suffix = c(".query", ".subject"))
#> DataFrame with 2 rows and 6 columns
#> granges.query granges.subject name.query score.query name.subject
#> <GRanges> <GRanges> <character> <numeric> <character>
#> 1 chr1:11-21:+ chr1:91-101:- a1 1 b2
#> 2 chr1:101-200:- chr1:201-210:- a2 2 b4
#> score.subject
#> <integer>
#> 1 2
#> 2 4
pair_precede(query, subject, suffix = c(".query", ".subject"))
#> DataFrame with 2 rows and 6 columns
#> granges.query granges.subject name.query score.query name.subject
#> <GRanges> <GRanges> <character> <numeric> <character>
#> 1 chr1:11-21:+ chr1:91-101:- a1 1 b2
#> 2 chr1:101-200:- chr1:201-210:- a2 2 b4
#> score.subject
#> <integer>
#> 1 2
#> 2 4