Obtain the differences between transcript structure

to_diff() obtains the difference between exons from a set of transcripts to a reference transcript (ref_exons). This can be useful when visualizing the differences between transcript structure. to_diff() expects two sets of input exons; 1. exons - exons from any number of transcripts that will be compared to ref_exons and 2. ref_exons - exons from a single transcript which acts as the reference to compare against.

Usage

to_diff(exons, ref_exons, group_var = NULL)

Arguments

exons: data.frame() contains exons which can originate from multiple transcripts differentiated by group_var.
ref_exons: data.frame() contains exons that originate from a single transcript, which exons will be compared against.
group_var: character() if input data originates from more than 1 transcript, group_var must specify the column that differentiates transcripts (e.g. "transcript_id").

Value

data.frame() details the differences between exons and ref_exons.

Examples


library(magrittr)
library(ggplot2)

# to illustrate the package's functionality
# ggtranscript includes example transcript annotation
sod1_annotation %>% head()
#> # A tibble: 6 × 8
#>   seqnames  start    end strand type  gene_name transcript_name transcript_biot…
#>   <fct>     <int>  <int> <fct>  <fct> <chr>     <chr>           <chr>           
#> 1 21       3.17e7 3.17e7 +      gene  SOD1      NA              NA              
#> 2 21       3.17e7 3.17e7 +      tran… SOD1      SOD1-202        protein_coding  
#> 3 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 4 21       3.17e7 3.17e7 +      CDS   SOD1      SOD1-202        protein_coding  
#> 5 21       3.17e7 3.17e7 +      star… SOD1      SOD1-202        protein_coding  
#> 6 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  

# extract exons
sod1_exons <- sod1_annotation %>% dplyr::filter(type == "exon")
sod1_exons %>% head()
#> # A tibble: 6 × 8
#>   seqnames  start    end strand type  gene_name transcript_name transcript_biot…
#>   <fct>     <int>  <int> <fct>  <fct> <chr>     <chr>           <chr>           
#> 1 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 2 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 3 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 4 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 5 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-202        protein_coding  
#> 6 21       3.17e7 3.17e7 +      exon  SOD1      SOD1-204        processed_trans…

# for this example, let's compare transcripts to the MANE-select transcript
sod1_mane <- sod1_exons %>% dplyr::filter(transcript_name == "SOD1-201")
sod1_not_mane <- sod1_exons %>% dplyr::filter(transcript_name != "SOD1-201")

# to_diff() obtains the differences between the exons as ranges
sod1_diffs <- to_diff(
    exons = sod1_not_mane,
    ref_exons = sod1_mane,
    group_var = "transcript_name"
)

sod1_diffs %>% head()
#>   seqnames    start      end width strand type  diff_type transcript_name
#> 1       21 31659666 31659692    27      + diff not_in_ref        SOD1-202
#> 2       21 31659785 31659841    57      + diff     in_ref        SOD1-202
#> 3       21 31661549 31661734   186      + diff not_in_ref        SOD1-204
#> 4       21 31667342 31667375    34      + diff     in_ref        SOD1-204
#> 5       21 31668471 31668931   461      + diff     in_ref        SOD1-204
#> 6       21 31659693 31659708    16      + diff     in_ref        SOD1-203

# using geom_range(), it can be useful to visually overlay
# the differences on top of the transcript annotation
sod1_exons %>%
    ggplot(aes(
        xstart = start,
        xend = end,
        y = transcript_name
    )) +
    geom_range() +
    geom_intron(
        data = to_intron(sod1_exons, "transcript_name")
    ) +
    geom_range(
        data = sod1_diffs,
        ggplot2::aes(fill = diff_type),
        alpha = 0.2
    )