Title: | Extending tidy verbs to genomic interactions |
---|---|
Description: | Operate on `GInteractions` objects as tabular data using `dplyr`-like verbs. The functions and methods in `plyinteractions` provide a grammatical approach to manipulate `GInteractions`, to facilitate their integration in genomic analysis workflows. |
Authors: | Jacques Serizay [aut, cre] |
Maintainer: | Jacques Serizay <[email protected]> |
License: | Artistic-2.0 |
Version: | 1.5.0 |
Built: | 2024-12-18 04:20:08 UTC |
Source: | https://github.com/bioc/plyinteractions |
plyinteractions is a dplyr-like API to the GInteractions infrastructure in Bioconductor.
plyinteractions provides a consistent interface for importing and
wrangling genomic interactions from a variety of sources. The package
defines a grammar of genomic interactions manipulation through a set of
verbs. These verbs can be used to construct human-readable analysis
pipelines based on GInteractions
.
Group genomic interactions with group_by
;
Summarize grouped genomic interactions with summarize
;
Tally/count grouped genomic interactions with tally
and count
;
Modify genomic interactions with mutate
;
Subset genomic interactions with filter
using
<data-masking>
and logical expressions;
Pick out any columns from the associated metadata with select
using <tidy-select>
arguments;
Subset using indices with slice
;
Order genomic interactions with arrange
using categorical/numerical
variables.
For more details on the features of plyinteractions, read the vignette:
browseVignettes(package = "plyinteractions")
Maintainer: Jacques Serizay [email protected]
Useful links:
Report bugs at https://github.com/js2264/plyinteractions/issues
Appends distance between interaction anchors, using
InteractionSet::pairdist
add_pairdist(x, type = "mid", colname = "pairdist")
add_pairdist(x, type = "mid", colname = "pairdist")
x |
The query GInteractions |
type |
A character string specifying the type of distance to compute. Can take values of "mid", "gap", "span", "diag" or "intra". |
colname |
name of column to hold pair distance values |
The GInteractions with an additional column containing the distance between each pair of anchors.
gi <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr2 3000 3800 bedpe_example2 100 + -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "name", "score", "strand1", "strand2") ) |> as_ginteractions() add_pairdist(gi)
gi <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr2 3000 3800 bedpe_example2 100 + -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "name", "score", "strand1", "strand2") ) |> as_ginteractions() add_pairdist(gi)
Enhanced GInteractions getters
anchors1(x) anchors2(x) seqnames1(x) seqnames2(x) start1(x) start2(x) end1(x) end2(x) width1(x) width2(x) strand1(x) strand2(x) ranges1(x) ranges2(x) ## S4 method for signature 'GInteractions' x$name ## S4 method for signature 'GInteractions' anchors1(x) ## S4 method for signature 'GInteractions' anchors2(x) ## S4 method for signature 'GInteractions' seqnames1(x) ## S4 method for signature 'GInteractions' seqnames2(x) ## S4 method for signature 'GInteractions' start1(x) ## S4 method for signature 'GInteractions' start2(x) ## S4 method for signature 'GInteractions' end1(x) ## S4 method for signature 'GInteractions' end2(x) ## S4 method for signature 'GInteractions' width1(x) ## S4 method for signature 'GInteractions' width2(x) ## S4 method for signature 'GInteractions' strand1(x) ## S4 method for signature 'GInteractions' strand2(x) ## S4 method for signature 'GInteractions' ranges1(x) ## S4 method for signature 'GInteractions' ranges2(x)
anchors1(x) anchors2(x) seqnames1(x) seqnames2(x) start1(x) start2(x) end1(x) end2(x) width1(x) width2(x) strand1(x) strand2(x) ranges1(x) ranges2(x) ## S4 method for signature 'GInteractions' x$name ## S4 method for signature 'GInteractions' anchors1(x) ## S4 method for signature 'GInteractions' anchors2(x) ## S4 method for signature 'GInteractions' seqnames1(x) ## S4 method for signature 'GInteractions' seqnames2(x) ## S4 method for signature 'GInteractions' start1(x) ## S4 method for signature 'GInteractions' start2(x) ## S4 method for signature 'GInteractions' end1(x) ## S4 method for signature 'GInteractions' end2(x) ## S4 method for signature 'GInteractions' width1(x) ## S4 method for signature 'GInteractions' width2(x) ## S4 method for signature 'GInteractions' strand1(x) ## S4 method for signature 'GInteractions' strand2(x) ## S4 method for signature 'GInteractions' ranges1(x) ## S4 method for signature 'GInteractions' ranges2(x)
x |
a GInteractions object |
name |
The pattern or name of a column stored in the GInteractions metadata (mcols). |
One of the core GInteractions fields (e.g. seqnames1, start1, ...)
or one of the metadata columns when using $
.
Note that auto-completion works with $
.
gi <- data.frame( seqnames1 = 'chr1', start1 = 1, end1 = 10, seqnames2 = 'chr1', start2 = 2, end2 = 20 ) |> as_ginteractions() |> mutate(type = 'cis') anchors1(gi) anchors2(gi) seqnames1(gi) seqnames2(gi) start1(gi) start2(gi) end1(gi) end2(gi) width1(gi) width2(gi) ranges1(gi) ranges2(gi) strand1(gi) strand2(gi) gi$type
gi <- data.frame( seqnames1 = 'chr1', start1 = 1, end1 = 10, seqnames2 = 'chr1', start2 = 2, end2 = 20 ) |> as_ginteractions() |> mutate(type = 'cis') anchors1(gi) anchors2(gi) seqnames1(gi) seqnames2(gi) start1(gi) start2(gi) end1(gi) end2(gi) width1(gi) width2(gi) ranges1(gi) ranges2(gi) strand1(gi) strand2(gi) gi$type
For each interaction in a GInteractions
object, annotate
returns
the pairs of annotations from the GRanges
object it overlaps with.
annotate(x, y, by) annotate_directed(x, y, by) ## S4 method for signature 'GInteractions,GRanges,character' annotate(x, y, by) ## S4 method for signature 'GInteractions,GRanges,character' annotate_directed(x, y, by)
annotate(x, y, by) annotate_directed(x, y, by) ## S4 method for signature 'GInteractions,GRanges,character' annotate(x, y, by) ## S4 method for signature 'GInteractions,GRanges,character' annotate_directed(x, y, by)
x |
a GInteractions object |
y |
a GRanges object to extract annotations from |
by |
Column name from |
a GInteractions object with two extra metadata columns named
by.1
and by.2
.
#################################################################### # 1. Basic example #################################################################### gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 21 30 + chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() gr <- GenomicRanges::GRanges(c("chr1:20-30:+", "chr2:55-65:+")) |> plyranges::mutate(id = 1:2) annotate(gi, gr, by = 'id') annotate_directed(gi, gr, by = 'id') #################################################################### # 2. Match loops with tiled genomic bins #################################################################### data(GM12878_HiCCUPS) loops <- GM12878_HiCCUPS |> pin_by('first') |> anchor_center() |> mutate(width1 = 500) |> pin_by('second') |> anchor_center() |> mutate(width2 = 500) genomic_bins <- GenomeInfoDb::getChromInfoFromUCSC( 'hg19', assembled.molecules.only = TRUE, as.Seqinfo = TRUE ) |> GenomicRanges::tileGenome(tilewidth = 10000) |> unlist() |> plyranges::mutate(binID = seq_len(plyranges::n())) annotate(loops, genomic_bins, by = 'binID') |> select(starts_with('binID')) #################################################################### # 3. Annotate interactions by a set of regulatory elements #################################################################### data(ce10_ARCC) data(ce10_REs) annotate(ce10_ARCC, ce10_REs, by = 'annot') |> count(annot.1, annot.2) |> as.data.frame() |> dplyr::arrange(desc(n))
#################################################################### # 1. Basic example #################################################################### gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 21 30 + chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() gr <- GenomicRanges::GRanges(c("chr1:20-30:+", "chr2:55-65:+")) |> plyranges::mutate(id = 1:2) annotate(gi, gr, by = 'id') annotate_directed(gi, gr, by = 'id') #################################################################### # 2. Match loops with tiled genomic bins #################################################################### data(GM12878_HiCCUPS) loops <- GM12878_HiCCUPS |> pin_by('first') |> anchor_center() |> mutate(width1 = 500) |> pin_by('second') |> anchor_center() |> mutate(width2 = 500) genomic_bins <- GenomeInfoDb::getChromInfoFromUCSC( 'hg19', assembled.molecules.only = TRUE, as.Seqinfo = TRUE ) |> GenomicRanges::tileGenome(tilewidth = 10000) |> unlist() |> plyranges::mutate(binID = seq_len(plyranges::n())) annotate(loops, genomic_bins, by = 'binID') |> select(starts_with('binID')) #################################################################### # 3. Annotate interactions by a set of regulatory elements #################################################################### data(ce10_ARCC) data(ce10_REs) annotate(ce10_ARCC, ce10_REs, by = 'annot') |> count(annot.1, annot.2) |> as.data.frame() |> dplyr::arrange(desc(n))
The as_ginteractions
function looks for column names in
.data called seqnames{1,2}, start{1,2}, end{1,2}, and strand{1,2}
in order to construct a GInteractions object.
By default other columns in .data are placed into the mcols (metadata
columns) slot of the returned object.
as_ginteractions( .data, ..., keep.extra.columns = TRUE, starts.in.df.are.0based = FALSE )
as_ginteractions( .data, ..., keep.extra.columns = TRUE, starts.in.df.are.0based = FALSE )
.data |
A |
... |
Optional named arguments specifying which the columns in .data containin the core components a GInteractions object. |
keep.extra.columns |
TRUE or FALSE (the default). If TRUE, the columns in df that are not used to form the genomic ranges of the returned GRanges object are then returned as metadata columns on the object. Otherwise, they are ignored. |
starts.in.df.are.0based |
TRUE or FALSE (the default). If TRUE, then the start positions of the genomic ranges in df are considered to be 0-based and are converted to 1-based in the returned GRanges object. |
a GInteractions object.
InteractionSet::GInteractions()
#################################################################### # 1. GInteractions from bedpe files imported into a data.frame #################################################################### bedpe <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr1 3000 3800 bedpe_example2 100 + -", col.names = c( "chrom1", "start1", "end1", "chrom2", "start2", "end2", "name", "score", "strand1", "strand2")) bedpe |> as_ginteractions(seqnames1 = chrom1, seqnames2 = chrom2) #################################################################### # 2. GInteractions from standard pairs files imported into a data.frame #################################################################### # Note how the pairs are 0-based and no "end" field is provided # (the standard pairs file format does not have "end" fields) # We can provide width1 and width2 to fix this problem. pairs <- read.table(text = " pair1 chr1 10000 chr1 20000 + + pair2 chr1 50000 chr1 70000 + + pair3 chr1 60000 chr2 10000 + + pair4 chr1 30000 chr3 40000 + -", col.names = c( "pairID", "chr1", "pos1", "chr2", "pos2", "strand1", "strand2") ) pairs |> as_ginteractions( seqnames1 = chr1, start1 = pos1, width1 = 1000, seqnames2 = chr2, start2 = pos2, width2 = 1000, starts.in.df.are.0based = TRUE ) #################################################################### # 3. GInteractions from data.frame with extra fields #################################################################### df <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr1 3000 3800", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) df |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) df <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr1 3000 3800", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) df |> as_ginteractions( seqnames1 = chr1, seqnames2 = chr2, strand1 = '+', strand2 = '-' ) data.frame(type = "cis", count = 3) |> as_ginteractions( seqnames1 = 'chr1', start1 = 1, end1 = 10, seqnames2 = 'chr1', start2 = 40, end2 = 50 ) #################################################################### # 4. GInteractions from a real like pairs files #################################################################### pairsf <- system.file('extdata', 'pairs.gz', package = 'plyinteractions') pairs <- read.table(pairsf, comment.char = '#', header = FALSE) head(pairs) pairs |> as_ginteractions( seqnames1 = V2, start1 = V3, width1 = 1, strand1 = V6, seqnames2 = V4, start2 = V5, width2 = 1, strand2 = V7, starts.in.df.are.0based = TRUE )
#################################################################### # 1. GInteractions from bedpe files imported into a data.frame #################################################################### bedpe <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr1 3000 3800 bedpe_example2 100 + -", col.names = c( "chrom1", "start1", "end1", "chrom2", "start2", "end2", "name", "score", "strand1", "strand2")) bedpe |> as_ginteractions(seqnames1 = chrom1, seqnames2 = chrom2) #################################################################### # 2. GInteractions from standard pairs files imported into a data.frame #################################################################### # Note how the pairs are 0-based and no "end" field is provided # (the standard pairs file format does not have "end" fields) # We can provide width1 and width2 to fix this problem. pairs <- read.table(text = " pair1 chr1 10000 chr1 20000 + + pair2 chr1 50000 chr1 70000 + + pair3 chr1 60000 chr2 10000 + + pair4 chr1 30000 chr3 40000 + -", col.names = c( "pairID", "chr1", "pos1", "chr2", "pos2", "strand1", "strand2") ) pairs |> as_ginteractions( seqnames1 = chr1, start1 = pos1, width1 = 1000, seqnames2 = chr2, start2 = pos2, width2 = 1000, starts.in.df.are.0based = TRUE ) #################################################################### # 3. GInteractions from data.frame with extra fields #################################################################### df <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr1 3000 3800", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) df |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) df <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr1 3000 3800", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) df |> as_ginteractions( seqnames1 = chr1, seqnames2 = chr2, strand1 = '+', strand2 = '-' ) data.frame(type = "cis", count = 3) |> as_ginteractions( seqnames1 = 'chr1', start1 = 1, end1 = 10, seqnames2 = 'chr1', start2 = 40, end2 = 50 ) #################################################################### # 4. GInteractions from a real like pairs files #################################################################### pairsf <- system.file('extdata', 'pairs.gz', package = 'plyinteractions') pairs <- read.table(pairsf, comment.char = '#', header = FALSE) head(pairs) pairs |> as_ginteractions( seqnames1 = V2, start1 = V3, width1 = 1, strand1 = V6, seqnames2 = V4, start2 = V5, width2 = 1, strand2 = V7, starts.in.df.are.0based = TRUE )
Arrange a GInteractions by a column
## S3 method for class 'GInteractions' arrange(.data, ...)
## S3 method for class 'GInteractions' arrange(.data, ...)
.data |
a GInteractions object |
... |
Variables, or functions of variables. Use dplyr::desc() to sort a variable in descending order. |
a GInteractions object.
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr1 2 10 chr2 1 10 chr3 3 10 chr3 1 10 chr4 4 10 chr4 1 10 chr5 5 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(cis = seqnames1 == seqnames2, score = runif(5)*100, gc = runif(5)) gi #################################################################### # 1. Arrange GInteractions by a numerical column #################################################################### gi |> arrange(gc) #################################################################### # 2. Arrange GInteractions by a logical column #################################################################### gi |> arrange(cis) #################################################################### # 3. Arrange GInteractions by a factor #################################################################### gi |> mutate(rep = factor(c("rep1", "rep2", "rep1", "rep2", "rep1"))) |> arrange(rep) #################################################################### # 4. Combine sorting variables #################################################################### gi |> mutate(rep = factor(c("rep1", "rep2", "rep1", "rep2", "rep1"))) |> arrange(dplyr::desc(rep), score)
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr1 2 10 chr2 1 10 chr3 3 10 chr3 1 10 chr4 4 10 chr4 1 10 chr5 5 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(cis = seqnames1 == seqnames2, score = runif(5)*100, gc = runif(5)) gi #################################################################### # 1. Arrange GInteractions by a numerical column #################################################################### gi |> arrange(gc) #################################################################### # 2. Arrange GInteractions by a logical column #################################################################### gi |> arrange(cis) #################################################################### # 3. Arrange GInteractions by a factor #################################################################### gi |> mutate(rep = factor(c("rep1", "rep2", "rep1", "rep2", "rep1"))) |> arrange(rep) #################################################################### # 4. Combine sorting variables #################################################################### gi |> mutate(rep = factor(c("rep1", "rep2", "rep1", "rep2", "rep1"))) |> arrange(dplyr::desc(rep), score)
Count or tally GInteractions per group
## S3 method for class 'GroupedGInteractions' tally(x, wt = NULL, sort = FALSE, name = NULL) ## S3 method for class 'GroupedGInteractions' count(x, ..., wt = NULL, sort = FALSE, name = NULL) ## S3 method for class 'GInteractions' count(x, ..., wt = NULL, sort = FALSE, name = NULL)
## S3 method for class 'GroupedGInteractions' tally(x, wt = NULL, sort = FALSE, name = NULL) ## S3 method for class 'GroupedGInteractions' count(x, ..., wt = NULL, sort = FALSE, name = NULL) ## S3 method for class 'GInteractions' count(x, ..., wt = NULL, sort = FALSE, name = NULL)
x |
A grouped GInteractions object |
wt |
<
|
sort |
If |
name |
The name of the new column in the output. |
... |
< |
a S4Vectors::DataFrame()
object, with an added column with the count/tablly per group.
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Tally groups #################################################################### gi gi |> group_by(strand1) |> tally() gi |> group_by(type) |> tally() gi |> group_by(type) |> tally(wt = score) #################################################################### # 2. Count per groups #################################################################### gi |> count(type) gi |> group_by(type) |> count(strand1) gi |> group_by(type, strand1) |> count(wt = score)
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Tally groups #################################################################### gi gi |> group_by(strand1) |> tally() gi |> group_by(type) |> tally() gi |> group_by(type) |> tally(wt = score) #################################################################### # 2. Count per groups #################################################################### gi |> count(type) gi |> group_by(type) |> count(strand1) gi |> group_by(type, strand1) |> count(wt = score)
filter
Subset a GInteractions with tidyverse-like filter
## S3 method for class 'GInteractions' filter(.data, ...)
## S3 method for class 'GInteractions' filter(.data, ...)
.data |
a GInteractions object |
... |
Expressions that return a logical value, and are defined in terms of the variables in .data. If multiple expressions are included, they are combined with the & operator. Only rows for which all conditions evaluate to TRUE are kept. |
a GInteractions object.
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr1 2 10 chr2 1 10 chr3 3 10 chr3 1 10 chr4 4 10 chr4 1 10 chr5 5 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(cis = seqnames1 == seqnames2, score = runif(5)*100, gc = runif(5)) gi #################################################################### # 1. Filter metadata columns from GInteractions by condition #################################################################### gi |> filter(gc > 0.1) gi |> filter(gc > 0.1, score > 50) gi |> filter(cis) #################################################################### # 2. On-the-fly calculations #################################################################### gi gi |> filter(start1 >= start2 + 3) gi |> filter(score * gc > score * 0.5)
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr1 2 10 chr2 1 10 chr3 3 10 chr3 1 10 chr4 4 10 chr4 1 10 chr5 5 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(cis = seqnames1 == seqnames2, score = runif(5)*100, gc = runif(5)) gi #################################################################### # 1. Filter metadata columns from GInteractions by condition #################################################################### gi |> filter(gc > 0.1) gi |> filter(gc > 0.1, score > 50) gi |> filter(cis) #################################################################### # 2. On-the-fly calculations #################################################################### gi gi |> filter(start1 >= start2 + 3) gi |> filter(score * gc > score * 0.5)
Group GInteractions by columns
## S3 method for class 'GInteractions' group_by(.data, ..., .add = FALSE) ## S3 method for class 'DelegatingGInteractions' group_by(.data, ..., .add = FALSE) ## S3 method for class 'GroupedGInteractions' ungroup(x, ...)
## S3 method for class 'GInteractions' group_by(.data, ..., .add = FALSE) ## S3 method for class 'DelegatingGInteractions' group_by(.data, ..., .add = FALSE) ## S3 method for class 'GroupedGInteractions' ungroup(x, ...)
.data , x
|
a (Grouped)GInteractions object |
... |
Column(s) to group by. |
.add |
When FALSE, the default, group_by() will override existing groups. To add to the existing groups, use .add = TRUE. |
a GroupedGInteractions
object. When a
(Anchored)PinnedGInteractions
object is grouped, both anchoring and
pinning are dropped.
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Group by core column #################################################################### gi |> group_by(end1) gi |> group_by(end1, end2) |> group_data() #################################################################### # 2. Group by metadata column #################################################################### gi |> group_by(type) |> group_data() #################################################################### # 3. Combine core and metadata column grouping #################################################################### gi |> group_by(end1, type) gi |> group_by(end1, type) |> group_data() #################################################################### # 4. Create a new column and group by this new variable #################################################################### gi |> group_by(class = c(1, 2, 1, 2)) #################################################################### # 5. Replace or add groups to a GroupedGInteractions #################################################################### ggi <- gi |> group_by(class = c(1, 2, 1, 2)) ggi |> group_data() ggi |> group_by(type) |> group_data() ggi |> group_by(type, .add = TRUE) |> group_data() #################################################################### # 6. Ungroup GInteractions #################################################################### ggi <- gi |> group_by(type, class = c(1, 2, 1, 2)) ggi ungroup(ggi, type) ungroup(ggi, class)
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Group by core column #################################################################### gi |> group_by(end1) gi |> group_by(end1, end2) |> group_data() #################################################################### # 2. Group by metadata column #################################################################### gi |> group_by(type) |> group_data() #################################################################### # 3. Combine core and metadata column grouping #################################################################### gi |> group_by(end1, type) gi |> group_by(end1, type) |> group_data() #################################################################### # 4. Create a new column and group by this new variable #################################################################### gi |> group_by(class = c(1, 2, 1, 2)) #################################################################### # 5. Replace or add groups to a GroupedGInteractions #################################################################### ggi <- gi |> group_by(class = c(1, 2, 1, 2)) ggi |> group_data() ggi |> group_by(type) |> group_data() ggi |> group_by(type, .add = TRUE) |> group_data() #################################################################### # 6. Ungroup GInteractions #################################################################### ggi <- gi |> group_by(type, class = c(1, 2, 1, 2)) ggi ungroup(ggi, type) ungroup(ggi, class)
Mutate columns from a GInteractions object
## S3 method for class 'GInteractions' mutate(.data, ...)
## S3 method for class 'GInteractions' mutate(.data, ...)
.data |
a GInteractions object |
... |
Optional named arguments specifying which the columns in .data to create/modify. |
a GInteractions object.
gi <- read.table(text = " chr1 10 20 chr1 50 51 chr1 10 50 chr2 30 40", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) #################################################################### # 1. Add metadata columns to a GInteractions object #################################################################### gi |> mutate(type = c('cis', 'trans'), score = runif(2)) |> mutate(type2 = type) #################################################################### # 2. More complex, nested or inplace changes #################################################################### gi |> mutate(type = c('cis', 'trans'), score = runif(2)) |> mutate(type2 = type) |> mutate(count = c(1, 2), score = count * 2, new_col = paste0(type2, score)) #################################################################### # 3. Core GInteractions columns can also be modified #################################################################### gi |> mutate(start1 = 1, end1 = 10, width2 = 30, strand2 = c('-', '+')) # Note how the core columns are modified sequentially gi |> mutate(start1 = 1, end1 = 10) gi |> mutate(start1 = 1, end1 = 10, width1 = 50) #################################################################### # 4. Evaluating core GInteractions columns #################################################################### gi |> mutate( score = runif(2), cis = seqnames1 == seqnames2, distance = ifelse(cis, start2 - end1, NA) )
gi <- read.table(text = " chr1 10 20 chr1 50 51 chr1 10 50 chr2 30 40", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) #################################################################### # 1. Add metadata columns to a GInteractions object #################################################################### gi |> mutate(type = c('cis', 'trans'), score = runif(2)) |> mutate(type2 = type) #################################################################### # 2. More complex, nested or inplace changes #################################################################### gi |> mutate(type = c('cis', 'trans'), score = runif(2)) |> mutate(type2 = type) |> mutate(count = c(1, 2), score = count * 2, new_col = paste0(type2, score)) #################################################################### # 3. Core GInteractions columns can also be modified #################################################################### gi |> mutate(start1 = 1, end1 = 10, width2 = 30, strand2 = c('-', '+')) # Note how the core columns are modified sequentially gi |> mutate(start1 = 1, end1 = 10) gi |> mutate(start1 = 1, end1 = 10, width1 = 50) #################################################################### # 4. Evaluating core GInteractions columns #################################################################### gi |> mutate( score = runif(2), cis = seqnames1 == seqnames2, distance = ifelse(cis, start2 - end1, NA) )
rename
Rename columns from a GInteractions with tidyverse-like rename
## S3 method for class 'GInteractions' rename(.data, ...)
## S3 method for class 'GInteractions' rename(.data, ...)
.data |
a GInteractions object |
... |
Use |
a GInteractions object.
gi <- read.table(text = " chr1 10 20 chr1 50 51 chr1 10 50 chr2 30 40", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) |> mutate(type = c('cis', 'trans'), score = runif(2)) #################################################################### # 1. Rename metadata columns to a GInteractions object #################################################################### gi |> rename(interaction_type = type, GC = score)
gi <- read.table(text = " chr1 10 20 chr1 50 51 chr1 10 50 chr2 30 40", col.names = c("chr1", "start1", "end1", "chr2", "start2", "end2")) |> as_ginteractions(seqnames1 = chr1, seqnames2 = chr2) |> mutate(type = c('cis', 'trans'), score = runif(2)) #################################################################### # 1. Rename metadata columns to a GInteractions object #################################################################### gi |> rename(interaction_type = type, GC = score)
Select columns within GInteractions metadata columns
## S3 method for class 'GInteractions' select(.data, ..., .drop_ranges = FALSE)
## S3 method for class 'GInteractions' select(.data, ..., .drop_ranges = FALSE)
.data |
a GInteractions object |
... |
Integer indicating rows to keep. |
.drop_ranges |
if TRUE, returns a DataFrame object. In this case, it enables selection of any column including core GInteractions columns. |
a GInteractions object.
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr2 1 10 chr2 1 10 chr3 1 10 chr3 1 10 chr4 1 10 chr4 1 10 chr5 1 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(score = runif(5)*100, cis = TRUE, gc = runif(5)) #################################################################### # 1. Select metadata columns from GInteractions by index #################################################################### gi |> select(2, 1) gi |> select(-3) #################################################################### # 2. Select metadata columns from GInteractions by name #################################################################### gi |> select(gc, score) #################################################################### # 3. Select metadata columns from GInteractions with <tidy-select> #################################################################### gi |> select(contains('s')) gi |> select(matches('^s')) #################################################################### # 4. Select core and metadata columns with .drop_ranges = TRUE #################################################################### gi |> select(matches('^s'), .drop_ranges = TRUE)
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr2 1 10 chr2 1 10 chr3 1 10 chr3 1 10 chr4 1 10 chr4 1 10 chr5 1 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(score = runif(5)*100, cis = TRUE, gc = runif(5)) #################################################################### # 1. Select metadata columns from GInteractions by index #################################################################### gi |> select(2, 1) gi |> select(-3) #################################################################### # 2. Select metadata columns from GInteractions by name #################################################################### gi |> select(gc, score) #################################################################### # 3. Select metadata columns from GInteractions with <tidy-select> #################################################################### gi |> select(contains('s')) gi |> select(matches('^s')) #################################################################### # 4. Select core and metadata columns with .drop_ranges = TRUE #################################################################### gi |> select(matches('^s'), .drop_ranges = TRUE)
Slice a GInteractions rows by their index
## S3 method for class 'GInteractions' slice(.data, ...)
## S3 method for class 'GInteractions' slice(.data, ...)
.data |
a GInteractions object |
... |
Integer indicating rows to keep. |
a GInteractions object.
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr2 1 10 chr2 1 10 chr3 1 10 chr3 1 10 chr4 1 10 chr4 1 10 chr5 1 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() #################################################################### # 1. Slice a GInteractions #################################################################### gi |> slice(1, 2, 3) gi |> slice(-3) gi |> slice(1:2, 5:4)
gi <- read.table(text = " chr1 1 10 chr1 1 10 chr2 1 10 chr2 1 10 chr3 1 10 chr3 1 10 chr4 1 10 chr4 1 10 chr5 1 10 chr5 1 10", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() #################################################################### # 1. Slice a GInteractions #################################################################### gi |> slice(1, 2, 3) gi |> slice(-3) gi |> slice(1:2, 5:4)
Summarize GInteractions per group
## S3 method for class 'GroupedGInteractions' summarise(.data, ...) ## S3 method for class 'GroupedGInteractions' summarize(.data, ...)
## S3 method for class 'GroupedGInteractions' summarise(.data, ...) ## S3 method for class 'GroupedGInteractions' summarize(.data, ...)
.data |
a (grouped) GInteractions object |
... |
Name-value pairs of summary functions. The name will be the name of the variable in the result. |
a S4Vectors::DataFrame()
object:
The rows come from the underlying group_keys()
.
The columns are a combination of the grouping keys and the summary expressions that you provide.
GInteractions class is not preserved, as a call to summarize
fundamentally creates a new data frame
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Summarize a single column #################################################################### gi gi |> group_by(type) |> summarize(m = mean(score)) gi |> group_by(strand1) |> summarize(m = mean(score)) df <- gi |> group_by(strand1) |> summarize(m = mean(score), n = table(seqnames2)) df df$n #################################################################### # 2. Summarize by multiple columns #################################################################### gi |> group_by(strand1, seqnames2) |> summarise(m = mean(score), n = table(type))
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Summarize a single column #################################################################### gi gi |> group_by(type) |> summarize(m = mean(score)) gi |> group_by(strand1) |> summarize(m = mean(score)) df <- gi |> group_by(strand1) |> summarize(m = mean(score), n = table(seqnames2)) df df$n #################################################################### # 2. Summarize by multiple columns #################################################################### gi |> group_by(strand1, seqnames2) |> summarise(m = mean(score), n = table(type))
Manage GInteractions anchors with plyranges
## S3 method for class 'AnchoredPinnedGInteractions' anchor(x) ## S3 method for class 'AnchoredPinnedGInteractions' unanchor(x) ## S3 method for class 'PinnedGInteractions' anchor_start(x) ## S3 method for class 'PinnedGInteractions' anchor_end(x) ## S3 method for class 'PinnedGInteractions' anchor_center(x) ## S3 method for class 'PinnedGInteractions' anchor_3p(x) ## S3 method for class 'PinnedGInteractions' anchor_5p(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_start(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_end(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_center(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_3p(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_5p(x)
## S3 method for class 'AnchoredPinnedGInteractions' anchor(x) ## S3 method for class 'AnchoredPinnedGInteractions' unanchor(x) ## S3 method for class 'PinnedGInteractions' anchor_start(x) ## S3 method for class 'PinnedGInteractions' anchor_end(x) ## S3 method for class 'PinnedGInteractions' anchor_center(x) ## S3 method for class 'PinnedGInteractions' anchor_3p(x) ## S3 method for class 'PinnedGInteractions' anchor_5p(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_start(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_end(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_center(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_3p(x) ## S3 method for class 'AnchoredPinnedGInteractions' anchor_5p(x)
x |
A PinnedGInteractions object |
anchor_*
functions return an AnchoredPinnedGInteractions object.
anchor
returns a character string indicating where the pinned
anchors are anchored at.
unanchor
removes the anchoring for a AnchoredPinnedGInteractions object.
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Anchoring pinned genomic interactions with plyranges #################################################################### gi |> pin_by("second") |> anchor_end()
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Anchoring pinned genomic interactions with plyranges #################################################################### gi |> pin_by("second") |> anchor_end()
Count overlaps between a query GInteractions and a GRanges
## S3 method for class 'PinnedGInteractions' count_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' count_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'PinnedGInteractions' count_overlaps_directed(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' count_overlaps_directed(x, y, maxgap = -1L, minoverlap = 0L)
## S3 method for class 'PinnedGInteractions' count_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' count_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'PinnedGInteractions' count_overlaps_directed(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' count_overlaps_directed(x, y, maxgap = -1L, minoverlap = 0L)
x |
A (Pinned)GInteractions object |
y |
A GRanges object |
maxgap , minoverlap
|
See |
An integer vector of same length as x.
GInteractions
When using count_overlaps()
with a PinnedGInteractions
object,
only the pinned anchors are used to check for overlap with y
.
This is equivalent to specifying use.region="both"
in
InteractionSet::findOverlaps()
.
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Count overlaps between GInteractions and a subject GRanges #################################################################### count_overlaps(gi, gr) count_overlaps_directed(gi, gr) #################################################################### # 2. Count overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> count_overlaps(gr) gi |> pin_by("second") |> count_overlaps(gr) gi |> pin_by("first") |> count_overlaps_directed(gr) gi |> pin_by("second") |> count_overlaps_directed(gr)
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Count overlaps between GInteractions and a subject GRanges #################################################################### count_overlaps(gi, gr) count_overlaps_directed(gi, gr) #################################################################### # 2. Count overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> count_overlaps(gr) gi |> pin_by("second") |> count_overlaps(gr) gi |> pin_by("first") |> count_overlaps_directed(gr) gi |> pin_by("second") |> count_overlaps_directed(gr)
bedpe
or pairs
fileswrite_*
functions are provided to export a GInteractions
object into these two file formats. See 4DN documentation
(https://github.com/4dn-dcic/pairix/blob/master/pairs_format_specification.md)
and UCSC documentation
(https://bedtools.readthedocs.io/en/latest/content/general-usage.html#bedpe-format)
for more details.
write_bedpe(x, file, scores = NULL) write_pairs(x, file, seqlengths = GenomeInfoDb::seqlengths(x))
write_bedpe(x, file, scores = NULL) write_pairs(x, file, seqlengths = GenomeInfoDb::seqlengths(x))
x |
a GInteractions object. |
file |
path to a |
scores |
Name of column to extract scores from. |
seqlengths |
Named vector indicating the chromosome sizes. |
TRUE
gi <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr1 3000 3800 bedpe_example2 100 + -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "name", "score", "strand1", "strand2") ) |> as_ginteractions() write_bedpe(gi, 'gi.bedpe') write_pairs(gi, 'gi.pairs')
gi <- read.table(text = " chr1 100 200 chr1 5000 5100 bedpe_example1 30 + - chr1 1000 5000 chr1 3000 3800 bedpe_example2 100 + -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "name", "score", "strand1", "strand2") ) |> as_ginteractions() write_bedpe(gi, 'gi.bedpe') write_pairs(gi, 'gi.pairs')
Filter GInteractions overlapping with a GRanges
## S3 method for class 'PinnedGInteractions' filter_by_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' filter_by_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'PinnedGInteractions' filter_by_non_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' filter_by_non_overlaps(x, y, maxgap = -1L, minoverlap = 0L)
## S3 method for class 'PinnedGInteractions' filter_by_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' filter_by_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'PinnedGInteractions' filter_by_non_overlaps(x, y, maxgap = -1L, minoverlap = 0L) ## S3 method for class 'GInteractions' filter_by_non_overlaps(x, y, maxgap = -1L, minoverlap = 0L)
x |
A (Pinned)GInteractions object |
y |
A GRanges object |
maxgap , minoverlap
|
See |
An integer vector of same length as x.
GInteractions
When using filter_by_overlaps()
with a PinnedGInteractions
object,
only the pinned anchors are used to check for overlap with y
.
This is equivalent to specifying use.region="both"
in
InteractionSet::findOverlaps()
.
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2") ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Filter GInteractions overlapping with a subject GRanges #################################################################### filter_by_overlaps(gi, gr) filter_by_non_overlaps(gi, gr) #################################################################### # 2. Filter PinnedGInteractions overlapping with a subject GRanges #################################################################### gi |> pin_by("first") |> filter_by_overlaps(gr) gi |> pin_by("first") |> filter_by_non_overlaps(gr) gi |> pin_by("second") |> filter_by_overlaps(gr) gi |> pin_by("second") |> filter_by_non_overlaps(gr)
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2") ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Filter GInteractions overlapping with a subject GRanges #################################################################### filter_by_overlaps(gi, gr) filter_by_non_overlaps(gi, gr) #################################################################### # 2. Filter PinnedGInteractions overlapping with a subject GRanges #################################################################### gi |> pin_by("first") |> filter_by_overlaps(gr) gi |> pin_by("first") |> filter_by_non_overlaps(gr) gi |> pin_by("second") |> filter_by_overlaps(gr) gi |> pin_by("second") |> filter_by_non_overlaps(gr)
Find overlaps between a query GInteractions and a GRanges
## S3 method for class 'PinnedGInteractions' find_overlaps(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'GInteractions' find_overlaps(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'PinnedGInteractions' find_overlaps_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") ) ## S3 method for class 'GInteractions' find_overlaps_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") )
## S3 method for class 'PinnedGInteractions' find_overlaps(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'GInteractions' find_overlaps(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'PinnedGInteractions' find_overlaps_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") ) ## S3 method for class 'GInteractions' find_overlaps_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") )
x |
A (Pinned)GInteractions object |
y |
A GRanges object |
maxgap , minoverlap
|
See |
suffix |
Suffix to add to metadata
columns (character vector of length 2, default to |
a GInteractions object with rows corresponding to the GInteractions
in x
that overlap y
.
find_overlaps()
will search for any overlap between GInteractions
in x
and GRanges
in y
. It will return a GInteractions
object of length equal to the number of times x
overlaps y
.
This GInteractions
will have additional metadata columns
corresponding to the metadata from y
. find_overlaps_directed()
takes the strandness of each object into account.
GInteractions
When using find_overlaps()
with a PinnedGInteractions
object,
only the pinned anchors are used to check for overlap with y
.
This is equivalent to specifying use.region="both"
in
InteractionSet::findOverlaps()
.
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Find overlaps between GInteractions and a subject GRanges #################################################################### find_overlaps(gi, gr) find_overlaps_directed(gi, gr) #################################################################### # 2. Find overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> find_overlaps(gr) gi |> pin_by("second") |> find_overlaps(gr) gi |> pin_by("first") |> find_overlaps_directed(gr) gi |> pin_by("second") |> find_overlaps_directed(gr)
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2" ) ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Find overlaps between GInteractions and a subject GRanges #################################################################### find_overlaps(gi, gr) find_overlaps_directed(gi, gr) #################################################################### # 2. Find overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> find_overlaps(gr) gi |> pin_by("second") |> find_overlaps(gr) gi |> pin_by("first") |> find_overlaps_directed(gr) gi |> pin_by("second") |> find_overlaps_directed(gr)
Join overlaps between a query GInteractions and a GRanges
## S3 method for class 'PinnedGInteractions' join_overlap_left(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'GInteractions' join_overlap_left(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'PinnedGInteractions' join_overlap_left_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") ) ## S3 method for class 'GInteractions' join_overlap_left_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") )
## S3 method for class 'PinnedGInteractions' join_overlap_left(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'GInteractions' join_overlap_left(x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y")) ## S3 method for class 'PinnedGInteractions' join_overlap_left_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") ) ## S3 method for class 'GInteractions' join_overlap_left_directed( x, y, maxgap = -1L, minoverlap = 0L, suffix = c(".x", ".y") )
x |
A (Pinned)GInteractions object |
y |
A GRanges object |
maxgap , minoverlap
|
See |
suffix |
Suffix to add to metadata
columns (character vector of length 2, default to |
An integer vector of same length as x.
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2") ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Join overlaps between GInteractions and a subject GRanges #################################################################### join_overlap_left(gi, gr) join_overlap_left_directed(gi, gr) #################################################################### # 2. Join overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> join_overlap_left(gr) gi |> pin_by("first") |> join_overlap_left_directed(gr) gi |> pin_by("second") |> join_overlap_left(gr) gi |> pin_by("second") |> join_overlap_left_directed(gr)
gi <- read.table(text = " chr1 11 20 - chr1 21 30 + chr1 11 20 - chr1 51 55 + chr1 21 30 - chr1 51 55 + chr1 21 30 - chr2 51 60 +", col.names = c( "seqnames1", "start1", "end1", "strand1", "seqnames2", "start2", "end2", "strand2") ) |> as_ginteractions() |> mutate(id = 1:4, type = 'gi') gr <- GenomicRanges::GRanges( c("chr1:20-30:+", "chr2:55-65:-") ) |> plyranges::mutate(id = 1:2, type = 'gr') gi gr #################################################################### # 1. Join overlaps between GInteractions and a subject GRanges #################################################################### join_overlap_left(gi, gr) join_overlap_left_directed(gi, gr) #################################################################### # 2. Join overlaps between PinnedGInteractions and a subject GRanges #################################################################### gi |> pin_by("first") |> join_overlap_left(gr) gi |> pin_by("first") |> join_overlap_left_directed(gr) gi |> pin_by("second") |> join_overlap_left(gr) gi |> pin_by("second") |> join_overlap_left_directed(gr)
GInteractions grouping metadata
## S3 method for class 'GroupedGInteractions' group_data(.data) ## S3 method for class 'GroupedGInteractions' group_keys(.tbl, ...) ## S3 method for class 'GroupedGInteractions' group_indices(.data, ...) ## S3 method for class 'GInteractions' group_vars(x) ## S3 method for class 'GroupedGInteractions' group_vars(x) ## S3 method for class 'GroupedGInteractions' groups(x) ## S3 method for class 'GroupedGInteractions' group_size(x) ## S3 method for class 'GroupedGInteractions' n_groups(x)
## S3 method for class 'GroupedGInteractions' group_data(.data) ## S3 method for class 'GroupedGInteractions' group_keys(.tbl, ...) ## S3 method for class 'GroupedGInteractions' group_indices(.data, ...) ## S3 method for class 'GInteractions' group_vars(x) ## S3 method for class 'GroupedGInteractions' group_vars(x) ## S3 method for class 'GroupedGInteractions' groups(x) ## S3 method for class 'GroupedGInteractions' group_size(x) ## S3 method for class 'GroupedGInteractions' n_groups(x)
.data , .tbl , x
|
a GInteractions object |
... |
Ignored. |
a GInteractions object.
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) ggi <- gi |> group_by(end1) ggi group_data(ggi) group_keys(ggi) group_rows(ggi) group_indices(ggi) group_vars(ggi) groups(ggi) group_size(ggi) n_groups(ggi)
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) ggi <- gi |> group_by(end1) ggi group_data(ggi) group_keys(ggi) group_rows(ggi) group_indices(ggi) group_vars(ggi) groups(ggi) group_size(ggi) n_groups(ggi)
Create a GInteractions object from a GRanges object, containing all possible entry pairs
pair_granges(x)
pair_granges(x)
x |
A GRanges object |
A GInteractions object
gr <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr2 3000 3800", col.names = c( "seqnames", "start", "end" )) |> plyranges::as_granges() pair_granges(gr)
gr <- read.table(text = " chr1 100 200 chr1 5000 5100 chr1 1000 5000 chr2 3000 3800", col.names = c( "seqnames", "start", "end" )) |> plyranges::as_granges() pair_granges(gr)
Pin GInteractions by anchors set (anchors1 or anchors2).
pin(x, anchors) pin_by(x, anchors) pinned_anchors(x) unpin(x) ## S4 method for signature 'GroupedGInteractions,character' pin(x, anchors) ## S4 method for signature 'GroupedGInteractions,numeric' pin(x, anchors) ## S4 method for signature 'GInteractions,character' pin(x, anchors) ## S4 method for signature 'GInteractions,numeric' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,missing' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,character' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,numeric' pin(x, anchors) ## S4 method for signature 'AnchoredPinnedGInteractions,character' pin(x, anchors) ## S4 method for signature 'AnchoredPinnedGInteractions,numeric' pin(x, anchors) pin_first(x) pin_second(x) pin_anchors1(x) pin_anchors2(x) ## S4 method for signature 'AnchoredPinnedGInteractions' unpin(x) ## S4 method for signature 'PinnedGInteractions' unpin(x) ## S4 method for signature 'GInteractions' unpin(x) ## S4 method for signature 'PinnedGInteractions' pinned_anchors(x) ## S4 method for signature 'AnchoredPinnedGInteractions' pinned_anchors(x)
pin(x, anchors) pin_by(x, anchors) pinned_anchors(x) unpin(x) ## S4 method for signature 'GroupedGInteractions,character' pin(x, anchors) ## S4 method for signature 'GroupedGInteractions,numeric' pin(x, anchors) ## S4 method for signature 'GInteractions,character' pin(x, anchors) ## S4 method for signature 'GInteractions,numeric' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,missing' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,character' pin(x, anchors) ## S4 method for signature 'PinnedGInteractions,numeric' pin(x, anchors) ## S4 method for signature 'AnchoredPinnedGInteractions,character' pin(x, anchors) ## S4 method for signature 'AnchoredPinnedGInteractions,numeric' pin(x, anchors) pin_first(x) pin_second(x) pin_anchors1(x) pin_anchors2(x) ## S4 method for signature 'AnchoredPinnedGInteractions' unpin(x) ## S4 method for signature 'PinnedGInteractions' unpin(x) ## S4 method for signature 'GInteractions' unpin(x) ## S4 method for signature 'PinnedGInteractions' pinned_anchors(x) ## S4 method for signature 'AnchoredPinnedGInteractions' pinned_anchors(x)
x |
a GInteractions object |
anchors |
Anchors to pin on ("first" or "second") |
pin_*
functions return a PinnedGInteractions object.
pin
returns a numerical value indicating which set of anchors is pinned.
unpin
removes the pinning of a PinnedGInteractions object.
pinned_anchors
returns an (Anchored)GenomicRanges object corresponding
to the pinned anchors of a PinnedGInteractions object.
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Pin by first anchors #################################################################### gi |> pin_by("first") gi |> pin_first() gi |> pin_anchors1() #################################################################### # 2. Pin by second anchors #################################################################### gi |> pin_by("second") gi |> pin_second() gi |> pin_anchors2() #################################################################### # 3. Unpin #################################################################### gi |> pin("second") |> unpin()
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Pin by first anchors #################################################################### gi |> pin_by("first") gi |> pin_first() gi |> pin_anchors1() #################################################################### # 2. Pin by second anchors #################################################################### gi |> pin_by("second") gi |> pin_second() gi |> pin_anchors2() #################################################################### # 3. Unpin #################################################################### gi |> pin("second") |> unpin()
Generate flanking regions from pinned anchors of a GInteractions object with plyranges
flank_downstream(x, width) ## S3 method for class 'Ranges' flank_downstream(x, width) ## S3 method for class 'PinnedGInteractions' flank_downstream(x, width) flank_upstream(x, width) ## S3 method for class 'Ranges' flank_upstream(x, width) ## S3 method for class 'PinnedGInteractions' flank_upstream(x, width) flank_right(x, width) ## S3 method for class 'Ranges' flank_right(x, width) ## S3 method for class 'PinnedGInteractions' flank_right(x, width) flank_left(x, width) ## S3 method for class 'Ranges' flank_left(x, width) ## S3 method for class 'PinnedGInteractions' flank_left(x, width)
flank_downstream(x, width) ## S3 method for class 'Ranges' flank_downstream(x, width) ## S3 method for class 'PinnedGInteractions' flank_downstream(x, width) flank_upstream(x, width) ## S3 method for class 'Ranges' flank_upstream(x, width) ## S3 method for class 'PinnedGInteractions' flank_upstream(x, width) flank_right(x, width) ## S3 method for class 'Ranges' flank_right(x, width) ## S3 method for class 'PinnedGInteractions' flank_right(x, width) flank_left(x, width) ## S3 method for class 'Ranges' flank_left(x, width) ## S3 method for class 'PinnedGInteractions' flank_left(x, width)
x |
a PinnedGInteractions object |
width |
The width of the flanking region relative to the ranges in x. Either an integer vector of length 1 or an integer vector the same length as x. The width can be negative in which case the flanking region is reversed. |
A PinnedGInteractions object
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple flanking #################################################################### gi gi |> pin_by("first") |> flank_left(-2) gi |> pin_by("second") |> flank_upstream(4) #################################################################### # 2. Chained flanking of each set of anchors #################################################################### gi |> pin_by("first") |> flank_left(2) |> pin_by("second") |> flank_right(2)
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple flanking #################################################################### gi gi |> pin_by("first") |> flank_left(-2) gi |> pin_by("second") |> flank_upstream(4) #################################################################### # 2. Chained flanking of each set of anchors #################################################################### gi |> pin_by("first") |> flank_left(2) |> pin_by("second") |> flank_right(2)
Shift pinned anchors of a GInteractions object with plyranges
shift_downstream(x, shift) ## S3 method for class 'Ranges' shift_downstream(x, shift) ## S3 method for class 'PinnedGInteractions' shift_downstream(x, shift) shift_upstream(x, shift) ## S3 method for class 'Ranges' shift_upstream(x, shift) ## S3 method for class 'PinnedGInteractions' shift_upstream(x, shift) shift_right(x, shift) ## S3 method for class 'Ranges' shift_right(x, shift) ## S3 method for class 'PinnedGInteractions' shift_right(x, shift) shift_left(x, shift) ## S3 method for class 'Ranges' shift_left(x, shift) ## S3 method for class 'PinnedGInteractions' shift_left(x, shift)
shift_downstream(x, shift) ## S3 method for class 'Ranges' shift_downstream(x, shift) ## S3 method for class 'PinnedGInteractions' shift_downstream(x, shift) shift_upstream(x, shift) ## S3 method for class 'Ranges' shift_upstream(x, shift) ## S3 method for class 'PinnedGInteractions' shift_upstream(x, shift) shift_right(x, shift) ## S3 method for class 'Ranges' shift_right(x, shift) ## S3 method for class 'PinnedGInteractions' shift_right(x, shift) shift_left(x, shift) ## S3 method for class 'Ranges' shift_left(x, shift) ## S3 method for class 'PinnedGInteractions' shift_left(x, shift)
x |
a PinnedGInteractions object |
shift |
The amount to move the genomic interval in the Ranges object by. Either a non-negative integer vector of length 1 or an integer vector the same length as x. |
A PinnedGInteractions object
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple shifting #################################################################### gi gi |> pin_by("first") |> shift_left(15) gi |> pin_by("second") |> shift_downstream(10) #################################################################### # 2. Chained shifting of each set of anchors #################################################################### gi |> pin_by("first") |> shift_downstream(20) |> pin_by("second") |> shift_upstream(20)
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple shifting #################################################################### gi gi |> pin_by("first") |> shift_left(15) gi |> pin_by("second") |> shift_downstream(10) #################################################################### # 2. Chained shifting of each set of anchors #################################################################### gi |> pin_by("first") |> shift_downstream(20) |> pin_by("second") |> shift_upstream(20)
Stretch pinned anchors of a GInteractions object with plyranges
## S3 method for class 'AnchoredPinnedGInteractions' stretch(x, extend) ## S3 method for class 'PinnedGInteractions' stretch(x, extend)
## S3 method for class 'AnchoredPinnedGInteractions' stretch(x, extend) ## S3 method for class 'PinnedGInteractions' stretch(x, extend)
x |
a PinnedGInteractions object |
extend |
The amount to alter the width of a Ranges object by. Either an integer vector of length 1 or an integer vector the same length as x. |
A PinnedGInteractions object
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple stretching #################################################################### gi gi |> pin_by("first") |> anchor_start() |> stretch(15) gi |> pin_by("second") |> anchor_center() |> stretch(10) gi |> pin_by("second") |> anchor_3p() |> stretch(20) #################################################################### # 2. Chained stretching of each set of anchors #################################################################### gi |> pin_by("first") |> anchor_start() |> stretch(20) |> pin_by("second") |> stretch(20)
gi <- read.table(text = " chr1 11 20 chr1 21 30 + + chr1 11 20 chr1 51 55 + + chr1 11 30 chr1 51 55 - - chr1 11 30 chr2 51 60 - -", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2", "strand1", "strand2") ) |> as_ginteractions() |> mutate(score = runif(4), type = c('cis', 'cis', 'cis', 'trans')) #################################################################### # 1. Simple stretching #################################################################### gi gi |> pin_by("first") |> anchor_start() |> stretch(15) gi |> pin_by("second") |> anchor_center() |> stretch(10) gi |> pin_by("second") |> anchor_3p() |> stretch(20) #################################################################### # 2. Chained stretching of each set of anchors #################################################################### gi |> pin_by("first") |> anchor_start() |> stretch(20) |> pin_by("second") |> stretch(20)
Replace anchors of a GInteractions
replace_anchors(x, id, value) ## S4 method for signature 'GInteractions,character,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'GInteractions,numeric,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'PinnedGInteractions,missing,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'AnchoredPinnedGInteractions,missing,GRanges' replace_anchors(x, id, value) ## S4 method for signature 'AnchoredPinnedGInteractions,numeric,GRanges' replace_anchors(x, id, value)
replace_anchors(x, id, value) ## S4 method for signature 'GInteractions,character,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'GInteractions,numeric,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'PinnedGInteractions,missing,GenomicRanges' replace_anchors(x, id, value) ## S4 method for signature 'AnchoredPinnedGInteractions,missing,GRanges' replace_anchors(x, id, value) ## S4 method for signature 'AnchoredPinnedGInteractions,numeric,GRanges' replace_anchors(x, id, value)
x |
a (Pinned)GInteractions object |
id |
Which anchors to replace ("first" or "second"). Ignored if the GInteractions is already pinned to a specific set of anchors. |
value |
A GRanges object vector the same length as x. |
a (Pinned)GInteractions object.
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Replace anchors of a GInteractions object #################################################################### gi |> replace_anchors(2, value = anchors1(gi)) gi |> replace_anchors(1, value = anchors2(gi)) gi |> replace_anchors(1, value = GenomicRanges::GRanges(c( "chr1:1-2", "chr1:2-3", "chr1:3-4", "chr1:4-5" ))) #################################################################### # 2. Replace anchors of a pinned GInteractions object #################################################################### gi |> pin_by(1) |> replace_anchors(value = anchors1(gi)) gi |> replace_anchors(1, value = anchors2(gi)) gi |> pin_by(1) |> replace_anchors(value = GenomicRanges::GRanges(c( "chr1:1-2", "chr1:2-3", "chr1:3-4", "chr1:4-5" ))) |> pin_by(2) |> replace_anchors(value = GenomicRanges::GRanges(c( "chr2:1-2", "chr2:2-3", "chr2:3-4", "chr2:4-5" )))
gi <- read.table(text = " chr1 11 20 chr1 21 30 chr1 11 20 chr1 51 55 chr1 11 30 chr1 51 55 chr1 11 30 chr2 51 60", col.names = c( "seqnames1", "start1", "end1", "seqnames2", "start2", "end2") ) |> as_ginteractions() |> mutate(type = c('cis', 'cis', 'cis', 'trans'), score = runif(4)) #################################################################### # 1. Replace anchors of a GInteractions object #################################################################### gi |> replace_anchors(2, value = anchors1(gi)) gi |> replace_anchors(1, value = anchors2(gi)) gi |> replace_anchors(1, value = GenomicRanges::GRanges(c( "chr1:1-2", "chr1:2-3", "chr1:3-4", "chr1:4-5" ))) #################################################################### # 2. Replace anchors of a pinned GInteractions object #################################################################### gi |> pin_by(1) |> replace_anchors(value = anchors1(gi)) gi |> replace_anchors(1, value = anchors2(gi)) gi |> pin_by(1) |> replace_anchors(value = GenomicRanges::GRanges(c( "chr1:1-2", "chr1:2-3", "chr1:3-4", "chr1:4-5" ))) |> pin_by(2) |> replace_anchors(value = GenomicRanges::GRanges(c( "chr2:1-2", "chr2:2-3", "chr2:3-4", "chr2:4-5" )))