tidygenomics

Tidy Verbs for Dealing with Genomic Data Frames

Description

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.

Installation

install.packages("tidygenomics")

# Or to get the latest development version
devtools::install_github("const-ae/tidygenomics")

Documentation

genome_intersect

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")

genome_subtract

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"))

genome_join_closest

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")

genome_cluster

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"))

genome_cluster(x1, by=c("chromosome", "start", "end"), max_distance=10)

genome_complement

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"))

genome_join

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")

fuzzyjoin::genome_join(x1, x2, by=c("chr", "start", "end"), mode="left")

fuzzyjoin::genome_join(x1, x2, by=c("chr", "start", "end"), mode="anti")

Inspiration

• tidyverse
• fuzzyjoin
• GenomicRanges
• bedtools

If you have any additional questions or encounter issues please raise them on the github page.