Tidy Verbs for Dealing with Genomic Data Frames
Handle genomic data within data frames just as you would with GRanges
.
This packages provides method to deal with genomics intervals the "tidy-way" which makes
it simpler to integrate in the the general data munging process. The API is inspired by the
popular bedtools and the genome_join() method from the fuzzyjoin package.
install.packages("tidygenomics")
Or to get the latest development version
devtools::install_github("const-ae/tidygenomics")
Joins 2 data frames based on their genomic overlap. Unlike the genome_join
function it updates the boundaries to reflect
the overlap of the regions.
x1 <- data.frame(id = 1:4,
chromosome = c("chr1", "chr1", "chr2", "chr2"),
start = c(100, 200, 300, 400),
end = c(150, 250, 350, 450))
x2 <- data.frame(id = 1:4,
chromosome = c("chr1", "chr2", "chr2", "chr1"),
start = c(140, 210, 400, 300),
end = c(160, 240, 415, 320))
genome_intersect(x1, x2, by=c("chromosome", "start", "end"), mode="both")
| id.x|chromosome | id.y| start| end| |----:|:----------|----:|-----:|---:| | 1|chr1 | 1| 140| 150| | 4|chr2 | 3| 400| 415|
Subtracts one data frame from the other. This can be used to split the x data frame into smaller areas.
x1 <- data.frame(id = 1:4,
chromosome = c("chr1", "chr1", "chr2", "chr1"),
start = c(100, 200, 300, 400),
end = c(150, 250, 350, 450))
x2 <- data.frame(id = 1:4,
chromosome = c("chr1", "chr2", "chr1", "chr1"),
start = c(120, 210, 300, 400),
end = c(125, 240, 320, 415))
genome_subtract(x1, x2, by=c("chromosome", "start", "end"))
| id|chromosome | start| end| |--:|:----------|-----:|---:| | 1|chr1 | 100| 119| | 1|chr1 | 126| 150| | 2|chr1 | 200| 250| | 3|chr2 | 300| 350| | 4|chr1 | 416| 450|
Joins 2 data frames based on their genomic location. If no exact overlap is found the next closest interval is used.
x1 <- data_frame(id = 1:4,
chr = c("chr1", "chr1", "chr2", "chr3"),
start = c(100, 200, 300, 400),
end = c(150, 250, 350, 450))
x2 <- data_frame(id = 1:4,
chr = c("chr1", "chr1", "chr1", "chr2"),
start = c(220, 210, 300, 400),
end = c(225, 240, 320, 415))
genome_join_closest(x1, x2, by=c("chr", "start", "end"), distance_column_name="distance", mode="left")
| id.x|chr.x | start.x| end.x| id.y|chr.y | start.y| end.y| distance| |----:|:-----|-------:|-----:|----:|:-----|-------:|-----:|--------:| | 1|chr1 | 100| 150| 2|chr1 | 210| 240| 59| | 2|chr1 | 200| 250| 1|chr1 | 220| 225| 0| | 2|chr1 | 200| 250| 2|chr1 | 210| 240| 0| | 3|chr2 | 300| 350| 4|chr2 | 400| 415| 49| | 4|chr3 | 400| 450| NA|NA | NA| NA| NA|
Add a new column with the cluster if 2 intervals are overlapping or are within the max_distance
.
x1 <- data.frame(id = 1:4, bla=letters[1:4],
chromosome = c("chr1", "chr1", "chr2", "chr1"),
start = c(100, 120, 300, 260),
end = c(150, 250, 350, 450))
genome_cluster(x1, by=c("chromosome", "start", "end"))
| id|bla |chromosome | start| end| cluster_id| |--:|:---|:----------|-----:|---:|----------:| | 1|a |chr1 | 100| 150| 0| | 2|b |chr1 | 120| 250| 0| | 3|c |chr2 | 300| 350| 2| | 4|d |chr1 | 260| 450| 1|
genome_cluster(x1, by=c("chromosome", "start", "end"), max_distance=10)
| id|bla |chromosome | start| end| cluster_id| |--:|:---|:----------|-----:|---:|----------:| | 1|a |chr1 | 100| 150| 0| | 2|b |chr1 | 120| 250| 0| | 3|c |chr2 | 300| 350| 1| | 4|d |chr1 | 260| 450| 0|
Calculates the complement of a genomic region.
x1 <- data.frame(id = 1:4,
chromosome = c("chr1", "chr1", "chr2", "chr1"),
start = c(100, 200, 300, 400),
end = c(150, 250, 350, 450))
genome_complement(x1, by=c("chromosome", "start", "end"))
|chromosome | start| end| |:----------|-----:|---:| |chr1 | 1| 99| |chr1 | 151| 199| |chr1 | 251| 399| |chr2 | 1| 299|
Classical join function based on the overlap of the interval. Implemented and maintained in the fuzzyjoin package and documented here only for completeness.
x1 <- data_frame(id = 1:4,
chr = c("chr1", "chr1", "chr2", "chr3"),
start = c(100, 200, 300, 400),
end = c(150, 250, 350, 450))
x2 <- data_frame(id = 1:4,
chr = c("chr1", "chr1", "chr1", "chr2"),
start = c(220, 210, 300, 400),
end = c(225, 240, 320, 415))
fuzzyjoin::genome_join(x1, x2, by=c("chr", "start", "end"), mode="inner")
| id.x|chr.x | start.x| end.x| id.y|chr.y | start.y| end.y| |----:|:-----|-------:|-----:|----:|:-----|-------:|-----:| | 2|chr1 | 200| 250| 1|chr1 | 220| 225| | 2|chr1 | 200| 250| 2|chr1 | 210| 240|
fuzzyjoin::genome_join(x1, x2, by=c("chr", "start", "end"), mode="left")
| id.x|chr.x | start.x| end.x| id.y|chr.y | start.y| end.y| |----:|:-----|-------:|-----:|----:|:-----|-------:|-----:| | 1|chr1 | 100| 150| NA|NA | NA| NA| | 2|chr1 | 200| 250| 1|chr1 | 220| 225| | 2|chr1 | 200| 250| 2|chr1 | 210| 240| | 3|chr2 | 300| 350| NA|NA | NA| NA| | 4|chr3 | 400| 450| NA|NA | NA| NA|
fuzzyjoin::genome_join(x1, x2, by=c("chr", "start", "end"), mode="anti")
| id|chr | start| end| |--:|:----|-----:|---:| | 1|chr1 | 100| 150| | 3|chr2 | 300| 350| | 4|chr3 | 400| 450|
If you have any additional questions or encounter issues please raise them on the github page.
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