1 Introduction

The plyinteractions package introduces tidy methods for the GInteractions class defined in the InteractionSet package (Lun, Perry, and Ing-Simmons, 2016).

1.1 `GInteractions` objects

GInteractions are objects describing interactions between two parallel sets of genomic ranges.

library(GenomicRanges)
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library(InteractionSet)
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anchor1 <- GRanges("chr1:10-20:+")
anchor2 <- GRanges("chr1:50-60:-")
gi <- GInteractions(anchor1, anchor2)

gi
#> GInteractions object with 1 interaction and 0 metadata columns:
#>       seqnames1   ranges1     seqnames2   ranges2
#>           <Rle> <IRanges>         <Rle> <IRanges>
#>   [1]      chr1     10-20 ---      chr1     50-60
#>   -------
#>   regions: 2 ranges and 0 metadata columns
#>   seqinfo: 1 sequence from an unspecified genome; no seqlengths

The InteractionSet package provides basic methods to interact with this class, but does not support tidy grammar principles.

1.2 Tidy grammar principles

The grammar of tidy genomic data transformation defined in plyranges and available for GInteractions currently supports:

dplyr verbs (for GInteractions and GroupedGInteractions):
- 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.
plyranges verbs (for PinnedGInteractions and AnchoredPinnedGInteractions):
- Stretch specific anchors of genomic interactions to a given width with stretch();
- anchor_*() functions to control how stretching is performed;
- Shift specific anchors of genomic interactions with shift();
- Obtain flanking GRanges from specific anchors of genomic interactions with flank().

2 Importing genomic interactions in R

plyinteractions provides a consistent interface for importing genomic interactions from pairs and bedpe files into GInteractions in R, following grammar of tidy data manipulation defined in the tidyverse ecosystem.

2.1 From bed-like text files

Tidy genomic data maniuplation implies that we first parse genomic files stored on disk as tabular data frames.

## This uses an example `bedpe` file provided in the `rtracklayer` package
bedpe_file <- system.file("tests", "test.bedpe", package = "rtracklayer")
bedpe_df <- read.delim(bedpe_file, header = FALSE, sep = '\t')

bedpe_df
#>      V1        V2        V3    V4        V5        V6                      V7 V8 V9 V10
#> 1  chr7 118965072 118965122  chr7 118970079 118970129 TUPAC_0001:3:1:0:1452#0 37  +   -
#> 2 chr11  46765606  46765656 chr10  46769934  46769984 TUPAC_0001:3:1:0:1472#0 37  +   -
#> 3 chr20  54704674  54704724 chr20  54708987  54709037 TUPAC_0001:3:1:1:1833#0 37  +   -

Genomic interactions in tabular format are not easy to manipulate. We can easily parse a data.frame into a GInteractions object using the as_ginteractions() function.

library(plyinteractions)
#> 
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#> The following object is masked from 'package:matrixStats':
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gi <- bedpe_df |> 
    as_ginteractions(
        seqnames1 = V1, start1 = V2, end1 = V3, strand1 = V9, 
        seqnames2 = V4, start2 = V5, end2 = V6, strand2 = V10, 
        starts.in.df.are.0based = TRUE
    )
#> Warning in .merge_two_Seqinfo_objects(x, y): Each of the 2 combined objects has sequence levels not in the other:
#>   - in 'x': chr11
#>   - in 'y': chr10
#>   Make sure to always combine/compare objects based on the same reference
#>   genome (use suppressWarnings() to suppress this warning).

gi
#> GInteractions object with 3 interactions and 2 metadata columns:
#>       seqnames1             ranges1 strand1     seqnames2             ranges2 strand2 |                     V7        V8
#>           <Rle>           <IRanges>   <Rle>         <Rle>           <IRanges>   <Rle> |            <character> <integer>
#>   [1]      chr7 118965073-118965122       + ---      chr7 118970080-118970129       - | TUPAC_0001:3:1:0:145..        37
#>   [2]     chr11   46765607-46765656       + ---     chr10   46769935-46769984       - | TUPAC_0001:3:1:0:147..        37
#>   [3]     chr20   54704675-54704724       + ---     chr20   54708988-54709037       - | TUPAC_0001:3:1:1:183..        37
#>   -------
#>   regions: 6 ranges and 0 metadata columns
#>   seqinfo: 4 sequences from an unspecified genome; no seqlengths

The columns containing information for core fields of the future GInteractions object (e.g. seqnames1, strand2, …) can be specified using the key = value (supported by quasiquotation).

2.2 From `pairs` files

The pairs file format has been formally defined by the 4DN consortium. Its specifications are available here.

It can be imported in R as a data.frame using read.delim() or any other tabular data import functions (including fread() or vroom() for larger files), and readily coerced into GInteractions with as_ginteractions().

## This uses an example `pairs` file provided in this package
pairs_file <- system.file('extdata', 'pairs.gz', package = 'plyinteractions') 
pairs_df <- read.delim(pairs_file, sep = "\t", header = FALSE, comment.char = "#")
head(pairs_df)
#>                                           V1 V2  V3 V4     V5 V6 V7   V8   V9
#> 1  NS500150:527:HHGYNBGXF:3:21611:19085:3986 II 105 II  48548  +  - 1358 1681
#> 2  NS500150:527:HHGYNBGXF:4:13604:19734:2406 II 113 II  45003  -  + 1358 1658
#> 3 NS500150:527:HHGYNBGXF:2:11108:25178:11036 II 119 II 687251  -  + 1358 5550
#> 4   NS500150:527:HHGYNBGXF:1:22301:8468:1586 II 160 II  26124  +  - 1358 1510
#> 5  NS500150:527:HHGYNBGXF:4:23606:24037:2076 II 169 II  39052  +  + 1358 1613
#> 6  NS500150:527:HHGYNBGXF:1:12110:9220:19806 II 177 II  10285  +  - 1358 1416
pairs <- as_ginteractions(pairs_df, 
    seqnames1 = V2, start1 = V3, strand1 = V6, 
    seqnames2 = V4, start2 = V5, strand2 = V7, 
    width1 = 1, width2 = 1, 
    keep.extra.columns = FALSE
)
pairs
#> GInteractions object with 50000 interactions and 0 metadata columns:
#>           seqnames1   ranges1 strand1     seqnames2   ranges2 strand2
#>               <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle>
#>       [1]        II       105       + ---        II     48548       -
#>       [2]        II       113       - ---        II     45003       +
#>       [3]        II       119       - ---        II    687251       +
#>       [4]        II       160       + ---        II     26124       -
#>       [5]        II       169       + ---        II     39052       +
#>       ...       ...       ...     ... ...       ...       ...     ...
#>   [49996]        II     86996       + ---        II    487591       +
#>   [49997]        II     86997       + ---        II     96353       -
#>   [49998]        II     86997       + ---        II    114748       -
#>   [49999]        II     86998       + ---        II     88955       +
#>   [50000]        II     86999       + ---        II     87513       +
#>   -------
#>   regions: 62911 ranges and 0 metadata columns
#>   seqinfo: 1 sequence from an unspecified genome; no seqlengths

2.3 Reverting from `GInteractions` to tabular data frames

The reverse operation to coerce GInteractions back to a tabular form is also possible using the as_tibble() function from the tibble package:

tibble::as_tibble(gi)
#> # A tibble: 3 × 12
#>   seqnames1    start1      end1 width1 strand1 seqnames2    start2      end2 width2 strand2 V7                         V8
#>   <fct>         <int>     <int>  <int> <fct>   <fct>         <int>     <int>  <int> <fct>   <chr>                   <int>
#> 1 chr7      118965073 118965122     50 +       chr7      118970080 118970129     50 -       TUPAC_0001:3:1:0:1452#0    37
#> 2 chr11      46765607  46765656     50 +       chr10      46769935  46769984     50 -       TUPAC_0001:3:1:0:1472#0    37
#> 3 chr20      54704675  54704724     50 +       chr20      54708988  54709037     50 -       TUPAC_0001:3:1:1:1833#0    37

3 Getter functions

3.1 `anchors{12}`

A GInteractions object consists of two sets of anchors: anchors1 and anchors2. Each set can be accessed with the corresponding function (anchors1() or anchors2()):

gi <- read.table(text = "
chr1 1 10 chr1 1 15 + + cis
chr1 6 15 chr1 1 20 + + cis
chr1 6 20 chr1 6 30 - - cis
chr1 11 30 chr2 11 30 - - trans",
col.names = c(
  "seqnames1", "start1", "end1", 
  "seqnames2", "start2", "end2", "strand1", "strand2", 
  "type")
) |> 
  as_ginteractions()

## `anchors` returns the two sets of anchors (i.e. "left" and "right" 
## loci) for each genomic interaction

anchors(gi)
#> $first
#> GRanges object with 4 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-10      +
#>   [2]     chr1      6-15      +
#>   [3]     chr1      6-20      -
#>   [4]     chr1     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths
#> 
#> $second
#> GRanges object with 4 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-15      +
#>   [2]     chr1      1-20      +
#>   [3]     chr1      6-30      -
#>   [4]     chr2     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## `anchors1` and `anchors2` specifically return the "left" OR "right" 
## loci) for each genomic interaction

anchors1(gi)
#> GRanges object with 4 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-10      +
#>   [2]     chr1      6-15      +
#>   [3]     chr1      6-20      -
#>   [4]     chr1     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

anchors2(gi)
#> GRanges object with 4 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-15      +
#>   [2]     chr1      1-20      +
#>   [3]     chr1      6-30      -
#>   [4]     chr2     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

Important note: the term anchors, when used for GInteractions, refers to the “left-hand” or “right-hand” GRanges when looking at genomic interactions. This is different from the anchor term used in plyranges. This is due to the fact that “anchor” is used in the chromatin interaction field to refer to the ends of a potential chromatin loop.

3.2 Core `GInteractions` fields

seqnames(), start()/end(), width() and strand() return informative core fields of a GRanges object. Appending 1 or 2 to these functions allow the end-user to fetch the corresponding fields from GInteractions objects.

## Similarly to `GRanges` accessors, `seqnames`, `start`, `end`, `strand` and 
## `width` are all available for each set of `anchors` of a `GInteractions`. 

seqnames1(gi)
#> factor-Rle of length 4 with 1 run
#>   Lengths:    4
#>   Values : chr1
#> Levels(2): chr1 chr2

start1(gi)
#> [1]  1  6  6 11

end2(gi)
#> [1] 15 20 30 30

strand2(gi)
#> factor-Rle of length 4 with 2 runs
#>   Lengths: 2 2
#>   Values : + -
#> Levels(3): + - *

width2(gi)
#> [1] 15 20 25 20

3.3 Metadata columns

GInteractions contain associated metadata stored as a DataFrame which can be recovered using the standard mcols() function:

mcols(gi)
#> DataFrame with 4 rows and 1 column
#>          type
#>   <character>
#> 1         cis
#> 2         cis
#> 3         cis
#> 4       trans

Individual metadata columns can also be accessed using the $ notation. Auto-completion is enabled for this method.

gi$type
#> [1] "cis"   "cis"   "cis"   "trans"

3.4 Extra genomic-related informations

Accessor functions provided in the InteractionSet package (which defines the GInteractions class) are also available.

regions(gi)
#> GRanges object with 8 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-10      +
#>   [2]     chr1      1-15      +
#>   [3]     chr1      1-20      +
#>   [4]     chr1      6-15      +
#>   [5]     chr1      6-20      -
#>   [6]     chr1      6-30      -
#>   [7]     chr1     11-30      -
#>   [8]     chr2     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

seqinfo(gi)
#> Seqinfo object with 2 sequences from an unspecified genome; no seqlengths:
#>   seqnames seqlengths isCircular genome
#>   chr1             NA         NA   <NA>
#>   chr2             NA         NA   <NA>

4 Pinned (and anchored) `GInteractions`

The anchoring approach developed in the plyranges package allows handy control over the way a GRanges object is extended when using the stretch() function. To enable such workflow for GInteractions, two classes were defined: PinnedGInteractions and AnchoredPinnedGInteractions.

4.1 `PinnedGInteractions`

Pinning a GInteractions object is used to specify which set of anchors (i.e. anchors1 or anchors2) should be affected by plyranges functions.

## `pin_by` is used to pin a `GInteractions` on "first" (i.e. "left") or 
## "second" (i.e. "right") anchors. 

gi |> pin_by("first")
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

pgi <- gi |> pin_by("second")
pin(pgi)
#> [1] 2

pinned_anchors(pgi)
#> GRanges object with 4 ranges and 0 metadata columns:
#>       seqnames    ranges strand
#>          <Rle> <IRanges>  <Rle>
#>   [1]     chr1      1-15      +
#>   [2]     chr1      1-20      +
#>   [3]     chr1      6-30      -
#>   [4]     chr2     11-30      -
#>   -------
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

A pinned GInteractions object can be reverted back to a unpinned GInteractions object.

unpin(pgi)
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

4.2 `AnchoredPinnedGInteractions`

Some plyranges operations can work on “anchored" GRanges. To enable these operations either on anchors1 or anchors2 from a GInteractions object, the”pinned” anchors{12} of the GInteractions object can be further “anchored”.

gi |> pin_by("first") |> anchor_5p()
#> AnchoredPinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1 | Anchored by: 5p
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

5 `plyranges` operations on `GInteractions`

plyranges arithmetic functions are available for (Anchored)PinnedGInteractions objects.

Important note 1: GInteractions must be pinned to a specific anchor set (anchors1 or anchors2) for plyranges functions to work. Please use pin_by() function to pin GInteractions.

Important note 2: the stretch() function will behave on PinnedGInteractions and AnchoredPinnedGInteractions objects similarly to GRanges or AnchoredGRanges objects.

5.1 On `PinnedGInteractions` objects

plyinteractions extends the use of verbs developed in plyranges to manipulate GRanges objects, to ensure they work on GInteractions. The GInteractions must be “pinned” (using pin_by()) in order to specify which set of anchors should be affected by plyranges functions.

gi
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This pins the "first" (i.e. "left") anchors and strecthes them by 10bp

gi |> pin_by("first") |> stretch(10)
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1     -4-15       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      1-20       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      1-25       - ---      chr1      6-30       - |         cis
#>   [4]      chr1      6-35       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 7 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This pins the "first" (i.e. "left") anchors and shift them 
## by 20bp to the right

gi |> pin_by("first") |> shift_right(20)
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1     21-30       + ---      chr1      1-15       + |         cis
#>   [2]      chr1     26-35       + ---      chr1      1-20       + |         cis
#>   [3]      chr1     26-40       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     31-50       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This pins the "first" (i.e. "left") anchors and extracts 20bp 
## flanking these "first" anchors

gi |> pin_by("first") |> flank_right(20)
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1     11-30       + ---      chr1      1-15       + |         cis
#>   [2]      chr1     16-35       + ---      chr1      1-20       + |         cis
#>   [3]      chr1     21-40       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     31-50       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

5.2 On `AnchoredPinnedGInteractions` objects

When a pinned GInteractions is further anchored, stretching with plyranges relies on the anchoring:

## This pins the "first" (i.e. "left") anchors and strecthes them by 10bp, 
## with the "first" anchors being anchored at their **start**. 

gi |> pin_by("first") |> anchor_start() |> stretch(10)
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-20       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-25       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-30       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-40       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 6 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This pins the "first" (i.e. "left") anchors and strecthes them by 10bp, 
## with the "first" anchors being anchored at their **center**. 

gi |> pin_by("first") |> anchor_center() |> stretch(10)
#> PinnedGInteractions object with 4 interactions and 1 metadata column:
#> Pinned on: anchors1
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1     -4-15       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      1-20       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      1-25       - ---      chr1      6-30       - |         cis
#>   [4]      chr1      6-35       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 7 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

6 `dplyr` operations on `GInteractions`

plyinteractions provides a set of verbs for developing analysis pipelines based on GInteractions objects that represent genomic interactions. The verbs extend dplyr functionalities to operate on a GInteractions object as if it were a tabular data object.

6.1 Mutating columns

mutate() supports accessing other existing columns:

## This creates a new metadata column named `cis`

gi |> mutate(cis = seqnames1 == seqnames2)
#> GInteractions object with 4 interactions and 2 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type   cis
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <Rle>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis  TRUE
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis  TRUE
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis  TRUE
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans FALSE
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This creates a new metadata column named `both_chr`

gi |> mutate(both_chr = paste(seqnames1, seqnames2, sep = "_"))
#> GInteractions object with 4 interactions and 2 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type  both_chr
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>     <Rle>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis chr1_chr1
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis chr1_chr1
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis chr1_chr1
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans chr1_chr2
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This modifies `start1`, i.e. the `start` coordinates of the "first"
## (i.e. "left") anchors of the `GInteractions` object. 

gi |> mutate(start1 = 1)
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      1-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      1-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1      1-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 7 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

6.2 Grouping columns

group_by() supports accessing both core and metadata columns:

## This groups the `GInteractions` object using the `seqnames2` variable
## (i.e. the `seqnames` of the "second" anchors of the `GInteractions`). 

gi |> group_by(seqnames2)
#> GroupedGInteractions object with 4 interactions and 1 metadata column:
#> Groups: seqnames2 [2]
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This groups the `GInteractions` object by a new variable named `cis`

gi |> group_by(cis = seqnames1 == seqnames2)
#> GroupedGInteractions object with 4 interactions and 2 metadata columns:
#> Groups: cis [2]
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type   cis
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <Rle>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis  TRUE
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis  TRUE
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis  TRUE
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans FALSE
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This groups the `GInteractions` object by two variables, `seqnames2` 
## and the new variable `cis`

gi |> group_by(seqnames2, cis = seqnames1 == seqnames2)
#> GroupedGInteractions object with 4 interactions and 2 metadata columns:
#> Groups: seqnames2, cis [2]
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type   cis
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <Rle>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis  TRUE
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis  TRUE
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis  TRUE
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans FALSE
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

6.3 Summarizing columns

Summarizing grouped GInteractions with summarize() can be extremely powerful.

## This counts the number of occurences of each combination of the variables
## `strand1` and `strand2`

pairs |> count(strand1, strand2)
#> DataFrame with 4 rows and 3 columns
#>   strand1 strand2         n
#>     <Rle>   <Rle> <integer>
#> 1       +       +     14046
#> 2       +       -     10823
#> 3       -       +     10288
#> 4       -       -     14843

## This counts the number of pairs located on the same strand 
## or different strands

gi |> group_by(same_strand = strand1 == strand2) |> tally()
#> DataFrame with 1 row and 2 columns
#>   same_strand         n
#>         <Rle> <integer>
#> 1        TRUE         4

## This counts the number of pairs located on the same strand 
## or different strands

pairs |> group_by(same_strand = strand1 == strand2) |> 
    summarize(
        neg_strand = sum(strand1 == "-"), 
        pos_strand = sum(strand1 == "+")
    )
#> DataFrame with 2 rows and 3 columns
#>   same_strand neg_strand pos_strand
#>         <Rle>  <integer>  <integer>
#> 1       FALSE      10288      10823
#> 2        TRUE      14843      14046

6.4 Filtering columns

filter() supports logical expressions:

gi |> filter(seqnames1 == 'chr11')
#> GInteractions object with 0 interactions and 1 metadata column:
#>    seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>        <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

gi |> filter(start1 >= 1e8)
#> GInteractions object with 0 interactions and 1 metadata column:
#>    seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>        <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

gi |> filter(seqnames1 == seqnames2)
#> GInteractions object with 3 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

6.5 Selecting columns

select() supports <tidy-select> arguments:

## This only keeps the "type" column from the metadata columns, 
## using <tidy-select> methodology

gi |> select(type)
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

gi |> select(contains("typ"))
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

gi |> select(starts_with("ty"))
#> GInteractions object with 4 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

Note that core fields (e.g. seqnames1, strand2, …) cannot be retrieved using this approach, only metadata columns are parsed. Selecting a subset of core fields from a GInteractions would lead to loss of required information (the other non-selected core fields).

## This does not restrict to `seqnames1` and `seqnames2` columns. 

gi |> select(starts_with('seq')) 
#> GInteractions object with 4 interactions and 0 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle>
#>   [1]      chr1      1-10       + ---      chr1      1-15       +
#>   [2]      chr1      6-15       + ---      chr1      1-20       +
#>   [3]      chr1      6-20       - ---      chr1      6-30       -
#>   [4]      chr1     11-30       - ---      chr2     11-30       -
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

Forcing selection of core fields is still possible when using the .drop_ranges argument of select(). This results in the coercion of the selected columns into a DataFrame.

## This selects `seqnames1` and `seqnames2` columns but converts the output
## into a `DataFrame`.

gi |> select(starts_with('seq'), .drop_ranges = TRUE) 
#> DataFrame with 4 rows and 2 columns
#>   seqnames1 seqnames2
#>       <Rle>     <Rle>
#> 1      chr1      chr1
#> 2      chr1      chr1
#> 3      chr1      chr1
#> 4      chr1      chr2

6.6 Slicing rows

## This only retains specific pair indices

gi |> slice(1, 2)
#> GInteractions object with 2 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

gi |> slice(-3)
#> GInteractions object with 3 interactions and 1 metadata column:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis
#>   [3]      chr1     11-30       - ---      chr2     11-30       - |       trans
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

7 Overlapping operations on `GInteractions`

Several operlapping functions defined in plyranges are available for GInteractions:

find_overlaps();
count_overlaps();
filter_by_overlaps() and filter_by_non_overlaps();
join_overlap_left().

All these functions can take a GInteractions query and a GRanges subject to perform overlapping operations, and maxgap and minoverlap arguments are available to refine the query.

These functions are unstranded by default. find_overlaps(), count_overlaps() and join_overlap_left() functions have *_directed() counterparts for when strandness is required.

7.1 Overlapping `GInteractions`

overlapping methods defined for GInteractions have also been adapted to work in a “tidy” manner.

gr <- GRanges(c("chr1:25-30:-", "chr2:16-20:+"))
gi$id <- seq_len(length(gi))
gr$id <- seq_len(length(gr))

## This returns the `GInteractions` entries overlapping with a `GRanges`
## (with either of both anchors)

find_overlaps(gi, gr)
#> GInteractions object with 3 interactions and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1      6-20       - ---      chr1      6-30       - |         cis         3         1
#>   [2]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         1
#>   [3]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         2
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This overlap requires the same strandness between 
## the `GInteractions` anchors and the `GRanges` object

find_overlaps_directed(gi, gr)
#> GInteractions object with 2 interactions and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1      6-20       - ---      chr1      6-30       - |         cis         3         1
#>   [2]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         1
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This counts how many times each entry in a `GInteractions` object 
## overlaps with a `GRanges` object (with either of both anchors)

count_overlaps(gi, gr)
#> [1] 0 0 1 2

count_overlaps_directed(gi, gr)
#> [1] 0 0 1 1

## This filters a `GInteractions` object to only retain the entries 
## overlapping (or not) with a `GRanges` (with either of both anchors)

filter_by_overlaps(gi, gr)
#> GInteractions object with 2 interactions and 2 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type        id
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer>
#>   [1]      chr1      6-20       - ---      chr1      6-30       - |         cis         3
#>   [2]      chr1     11-30       - ---      chr2     11-30       - |       trans         4
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

filter_by_non_overlaps(gi, gr)
#> GInteractions object with 2 interactions and 2 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type        id
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis         1
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis         2
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This performs a left join between `GInteractions` entries and
## a `GRanges` of interest (with/without considering strandness)

join_overlap_left(gi, gr)
#> GInteractions object with 5 interactions and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis         1      <NA>
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis         2      <NA>
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis         3         1
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         1
#>   [5]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         2
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

join_overlap_left_directed(gi, gr)
#> GInteractions object with 4 interactions and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1      1-10       + ---      chr1      1-15       + |         cis         1      <NA>
#>   [2]      chr1      6-15       + ---      chr1      1-20       + |         cis         2      <NA>
#>   [3]      chr1      6-20       - ---      chr1      6-30       - |         cis         3         1
#>   [4]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         1
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

7.2 Overlapping pinned `GInteractions`

PinnedGInteractions can also be used in overlapping functions. In this case, only the pinned anchors are used when computing overlaps.

## This returns the `GInteractions` entries for which 
## the "first" anchor overlaps with a `GRanges`

gi |> pin_by("first") |> find_overlaps(gr)
#> GInteractions object with 1 interaction and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         1
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

## This returns the `GInteractions` entries for which 
## the "second" anchor overlaps with a `GRanges`

gi |> pin_by("second") |> find_overlaps(gr)
#> GInteractions object with 2 interactions and 3 metadata columns:
#>       seqnames1   ranges1 strand1     seqnames2   ranges2 strand2 |        type      id.x      id.y
#>           <Rle> <IRanges>   <Rle>         <Rle> <IRanges>   <Rle> | <character> <integer> <integer>
#>   [1]      chr1      6-20       - ---      chr1      6-30       - |         cis         3         1
#>   [2]      chr1     11-30       - ---      chr2     11-30       - |       trans         4         2
#>   -------
#>   regions: 8 ranges and 0 metadata columns
#>   seqinfo: 2 sequences from an unspecified genome; no seqlengths

8 Citing `plyinteractions`

We hope that plyinteractions will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you!

## Citation info
citation("plyinteractions")
#> To cite package 'plyinteractions' in publications use:
#> 
#>   Serizay J (2024). _plyinteractions: Extending tidy verbs to genomic interactions_. doi:10.18129/B9.bioc.plyinteractions <https://doi.org/10.18129/B9.bioc.plyinteractions>, R package version 1.5.0, <https://bioconductor.org/packages/plyinteractions>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {plyinteractions: Extending tidy verbs to genomic interactions},
#>     author = {Jacques Serizay},
#>     year = {2024},
#>     note = {R package version 1.5.0},
#>     url = {https://bioconductor.org/packages/plyinteractions},
#>     doi = {10.18129/B9.bioc.plyinteractions},
#>   }

9 Acknowledgments

The plyinteractions package introduces tidy methods for the GInteractions class defined in the InteractionSet package (Lun, Perry, and Ing-Simmons, 2016).

The plyinteractions package follows tidy principles defined for tabular data and genomic ranges:

dplyr (Wickham, François, Henry, Müller, and Vaughan, 2023)
rlang (Henry and Wickham, 2024)
plyranges (Lee, Stuart, Cook, Dianne, Lawrence, and Michael, 2019)

The plyinteractions package (Serizay, 2024) was written using the following resources:

R (R Core Team, 2024)
devtools
usethis

Supporting documentation was generated using the following resources:

BiocStyle (Oleś, 2024)
knitr (Xie, 2024)
RefManageR (McLean, 2017)
rmarkdown (Allaire, Xie, Dervieux, McPherson, Luraschi, Ushey, Atkins, Wickham, Cheng, Chang, and Iannone, 2024)

10 Reproducibility

R session information:

#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R Under development (unstable) (2024-10-21 r87258)
#>  os       Ubuntu 24.04.1 LTS
#>  system   x86_64, linux-gnu
#>  ui       X11
#>  language (EN)
#>  collate  C
#>  ctype    en_US.UTF-8
#>  tz       America/New_York
#>  date     2024-10-29
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11 Bibliography

[1] J. Allaire, Y. Xie, C. Dervieux, et al. rmarkdown: Dynamic Documents for R. R package version 2.28. 2024. URL: https://github.com/rstudio/rmarkdown.

[2] L. Henry and H. Wickham. rlang: Functions for Base Types and Core R and ‘Tidyverse’ Features. R package version 1.1.4. 2024. DOI: 10.32614/CRAN.package.rlang. URL: https://CRAN.R-project.org/package=rlang.

[3] Lee, Stuart, Cook, et al. “plyranges: a grammar of genomic data transformation”. In: Genome Biol. 20.1 (2019), p. 4. URL: http://dx.doi.org/10.1186/s13059-018-1597-8.

[4] A. T. L. Lun, M. Perry, and E. Ing-Simmons. “Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments”. In: F1000Res. 5 (2016), p. 950.

[5] M. W. McLean. “RefManageR: Import and Manage BibTeX and BibLaTeX References in R”. In: The Journal of Open Source Software (2017). DOI: 10.21105/joss.00338.

[6] A. Oleś. BiocStyle: Standard styles for vignettes and other Bioconductor documents. R package version 2.35.0. 2024. DOI: 10.18129/B9.bioc.BiocStyle. URL: https://bioconductor.org/packages/BiocStyle.

[7] R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria, 2024. URL: https://www.R-project.org/.

[8] J. Serizay. plyinteractions: Extending tidy verbs to genomic interactions. R package version 1.5.0. 2024. DOI: 10.18129/B9.bioc.plyinteractions. URL: https://bioconductor.org/packages/plyinteractions.

[9] H. Wickham, R. François, L. Henry, et al. dplyr: A Grammar of Data Manipulation. R package version 1.1.4. 2023. DOI: 10.32614/CRAN.package.dplyr. URL: https://CRAN.R-project.org/package=dplyr.

[10] Y. Xie. knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.48. 2024. URL: https://yihui.org/knitr/.

plyinteractions

29 October 2024

Package

1 Introduction

1.1 GInteractions objects

1.2 Tidy grammar principles

2 Importing genomic interactions in R

2.1 From bed-like text files

2.2 From pairs files

2.3 Reverting from GInteractions to tabular data frames

3 Getter functions

3.1 anchors{12}

3.2 Core GInteractions fields