svaRetro Quick Overview
2026-02-18
Contents
1 Introduction
This vignette outlines a workflow of detecting retrotransposed transcripts (RTs)
from Variant Call Format (VCF) using the svaRetro package.
2 Installation
The svaRetro package can be installed from Bioconductor as follows:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("svaRetro")3 Using GRanges for structural variants: a breakend-centric data structure
This package uses a breakend-centric event notation adopted from the
StructuralVariantAnnotation package. In short, breakends are stored in a
GRanges object with strand used to indicate breakpoint orientation, where
breakpoints are represented using a partner field containing the name of the
breakend at the other side of the breakend. This notation was chosen as it
simplifies the annotations of RTs which are detected at breakend-level.
4 Workflow
4.1 Loading data from VCF
VCF data is parsed into a VCF object using the readVCF function from the
Bioconductor package VariantAnnotation. Simple filters could be applied to a
VCF object to remove unwanted calls. The VCF object is then converted to a
GRanges object with breakend-centric notations using
StructuralVariantAnnotation. More information about VCF objects and
breakend-centric GRanges object can be found by
consulting the vignettes in the corresponding packages with
browseVignettes("VariantAnnotation") and
browseVignettes("StructuralVariantAnnotation").
library(StructuralVariantAnnotation)
library(VariantAnnotation)
library(svaRetro)
RT_vcf <- readVcf(system.file("extdata", "diploidSV.vcf", package = "svaRetro"))RT_gr <- StructuralVariantAnnotation::breakpointRanges(RT_vcf,
nominalPosition = TRUE
)
head(RT_gr)Note that StructuralVariantAnnotation requires the GRanges object to be
composed entirely of valid breakpoints. Please consult the vignette of the
StructuralVariantAnnotation package for ensuring breakpoint consistency.
4.2 Identifying Retrotransposed Transcripts
The package provides rtDetect to identify RTs using the provided SV calls.
This is achieved by detecting intronic deletions, which are breakpoints at
exon-intron (and intron-exon) boundaries of a transcript. Fusions consisting of
an exon boundary and a second genomic location are reported as potential
insertion sites. Due to the complexity of RT events, insertion sites can be
discovered on both left and right sides, only one side, or none at all.
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
library(dplyr)
hg19.genes <- TxDb.Hsapiens.UCSC.hg19.knownGene
RT <- rtDetect(RT_gr, hg19.genes, maxgap = 10, minscore = 0.8)The output is a list of GRanges object consisting of two sets of GRanges
calls, insSite and junctions, containing candidate insertion sites and
exon-exon junctions respectively. Candidate insertion sites are annotated by
the source transcripts and whether exon-exon junctions are detected for the
source transcripts. RT junction breakends are annotated by the UCSC exon IDs,
corresponding transcripts, and NCBI gene symbols.
RT$SKA3
#> $junctions
#> GRanges object with 14 ranges and 17 metadata columns:
#> seqnames ranges strand | paramRangeID REF ALT QUAL FILTER sourceId partner svtype svLen insSeq insLen event HOMLEN exon txs exons gene_symbol
#> <Rle> <IRanges> <Rle> | <factor> <character> <character> <numeric> <character> <character> <character> <character> <numeric> <character> <numeric> <character> <numeric> <integer> <list> <list> <list>
#> MantaDEL:245251:6:6:0:0:0_bp2 13 21729832 - | NA TCTGCAACAGATACAAATAA.. T 999 PASS MantaDEL:245251:6:6:.. MantaDEL:245251:6:6:.. DEL -542 0 <NA> 1 589252 ENST00000298260.8_4,ENST00000314759.6_11 589252 SKA3
#> MantaDEL:245251:5:8:0:0:0_bp2 13 21732061 - | NA G <DEL> 999 PASS MantaDEL:245251:5:8:.. MantaDEL:245251:5:8:.. DEL -2110 <NA> 0 <NA> 2 589253 ENST00000298260.8_4,ENST00000314759.6_11 589253 SKA3
#> MantaDEL:245251:5:9:0:0:0_bp2 13 21734038 - | NA A <DEL> 525 PASS MantaDEL:245251:5:9:.. MantaDEL:245251:5:9:.. DEL -1776 <NA> 0 <NA> 4 589254 ENST00000298260.8_4,ENST00000314759.6_11 589254 SKA3
#> MantaDEL:245251:7:10:0:0:0_bp2 13 21735929 - | NA T <DEL> 539 PASS MantaDEL:245251:7:10.. MantaDEL:245251:7:10.. DEL -1802 <NA> 0 <NA> 1 589255 ENST00000298260.8_4,ENST00000314759.6_11 589255 SKA3
#> MantaDEL:245251:4:11:0:0:0_bp2 13 21742127 - | NA A <DEL> 999 PASS MantaDEL:245251:4:11.. MantaDEL:245251:4:11.. DEL -6112 <NA> 0 <NA> 2 589256 ENST00000298260.8_4,ENST00000314759.6_11 589256 SKA3
#> ... ... ... ... . ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
#> MantaDEL:245251:5:9:0:0:0_bp1 13 21732261 + | NA A <DEL> 525 PASS MantaDEL:245251:5:9:.. MantaDEL:245251:5:9:.. DEL -1776 <NA> 0 <NA> 4 589253 ENST00000298260.8_4,ENST00000314759.6_11 589253 SKA3
#> MantaDEL:245251:7:10:0:0:0_bp1 13 21734126 + | NA T <DEL> 539 PASS MantaDEL:245251:7:10.. MantaDEL:245251:7:10.. DEL -1802 <NA> 0 <NA> 1 589254 ENST00000298260.8_4,ENST00000314759.6_11 589254 SKA3
#> MantaDEL:245251:4:11:0:0:0_bp1 13 21736014 + | NA A <DEL> 999 PASS MantaDEL:245251:4:11.. MantaDEL:245251:4:11.. DEL -6112 <NA> 0 <NA> 2 589255 ENST00000298260.8_4,ENST00000314759.6_11 589255 SKA3
#> MantaDEL:245251:3:4:0:0:0_bp1 13 21742538 + | NA A <DEL> 999 PASS MantaDEL:245251:3:4:.. MantaDEL:245251:3:4:.. DEL -3939 <NA> 0 <NA> 2 589256 ENST00000298260.8_4,ENST00000314759.6_11 589256,589257 SKA3
#> MantaDEL:245251:2:3:0:0:0_bp1 13 21746642 + | NA T <DEL> 999 PASS MantaDEL:245251:2:3:.. MantaDEL:245251:2:3:.. DEL -3870 <NA> 0 <NA> 2 589258 ENST00000298260.8_4,ENST00000314759.6_11 589258,589259 SKA3
#> -------
#> seqinfo: 25 sequences (1 circular) from GRCh37.p13 genome
#>
#> $insSite
#> GRanges object with 0 ranges and 18 metadata columns:
#> seqnames ranges strand | paramRangeID REF ALT QUAL FILTER sourceId partner svtype svLen insSeq insLen event HOMLEN exons txs rtFound rtFoundSum gene_symbol
#> <Rle> <IRanges> <Rle> | <factor> <character> <character> <numeric> <character> <character> <character> <character> <numeric> <character> <numeric> <character> <numeric> <list> <list> <list> <logical> <list>
#> -------
#> seqinfo: 25 sequences (1 circular) from GRCh37.p13 genome5 Visualising breakpoint pairs via circos plots
One way of visualising RT is by circos plots. Here we use the package
circlize to demonstrate
the visualisation of insertion site and exon-exon junctions.
To generate a simple circos plot of RT event with SKA3 transcript:
library(circlize)
rt_chr_prefix <- c(RT$SKA3$junctions, RT$SKA3$insSite)
GenomeInfoDb::seqlevelsStyle(rt_chr_prefix) <- "UCSC"
pairs <- breakpointgr2pairs(rt_chr_prefix)
pairsTo see supporting breakpoints clearly, we generate the circos plot according to the loci of event.
circos.initializeWithIdeogram(
data.frame(
V1 = c("chr13", "chr11"),
V2 = c(21720000, 108585000),
V3 = c(21755000, 108586000),
V4 = c("q12.11", "q24.3"),
V5 = c("gneg", "gpos50")
)
)
circos.genomicLink(
as.data.frame(S4Vectors::first(pairs)),
as.data.frame(S4Vectors::second(pairs))
)
circos.clear()6 SessionInfo
sessionInfo()
#> R version 4.5.2 (2025-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.3 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.22-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0 LAPACK version 3.12.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_GB LC_COLLATE=C LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] circlize_0.4.17 dplyr_1.2.0 TxDb.Hsapiens.UCSC.hg19.knownGene_3.22.1 GenomicFeatures_1.62.0 AnnotationDbi_1.72.0 svaRetro_1.16.6 StructuralVariantAnnotation_1.26.0 VariantAnnotation_1.56.0 Rsamtools_2.26.0 Biostrings_2.78.0 XVector_0.50.0 SummarizedExperiment_1.40.0 Biobase_2.70.0 MatrixGenerics_1.22.0 matrixStats_1.5.0 rtracklayer_1.70.1 GenomicRanges_1.62.1 Seqinfo_1.0.0 IRanges_2.44.0 S4Vectors_0.48.0 BiocGenerics_0.56.0 generics_0.1.4 BiocStyle_2.38.0
#>
#> loaded via a namespace (and not attached):
#> [1] tidyselect_1.2.1 blob_1.3.0 bitops_1.0-9 fastmap_1.2.0 RCurl_1.98-1.17 GenomicAlignments_1.46.0 XML_3.99-0.22 digest_0.6.39 lifecycle_1.0.5 pwalign_1.6.0 KEGGREST_1.50.0 RSQLite_2.4.6 magrittr_2.0.4 compiler_4.5.2 rlang_1.1.7 sass_0.4.10 tools_4.5.2 yaml_2.3.12 knitr_1.51 S4Arrays_1.10.1 bit_4.6.0 curl_7.0.0 DelayedArray_0.36.0 abind_1.4-8 BiocParallel_1.44.0 grid_4.5.2 colorspace_2.1-2 tinytex_0.58 cli_3.6.5 rmarkdown_2.30 crayon_1.5.3 otel_0.2.0 httr_1.4.8 rjson_0.2.23 DBI_1.2.3 cachem_1.1.0 stringr_1.6.0 assertthat_0.2.1 parallel_4.5.2
#> [40] BiocManager_1.30.27 restfulr_0.0.16 vctrs_0.7.1 Matrix_1.7-4 jsonlite_2.0.0 bookdown_0.46 bit64_4.6.0-1 magick_2.9.0 jquerylib_0.1.4 glue_1.8.0 codetools_0.2-20 shape_1.4.6.1 stringi_1.8.7 GenomeInfoDb_1.46.2 BiocIO_1.20.0 UCSC.utils_1.6.1 tibble_3.3.1 pillar_1.11.1 htmltools_0.5.9 BSgenome_1.78.0 R6_2.6.1 evaluate_1.0.5 lattice_0.22-9 png_0.1-8 cigarillo_1.0.0 memoise_2.0.1 bslib_0.10.0 Rcpp_1.1.1 SparseArray_1.10.8 org.Hs.eg.db_3.22.0 xfun_0.56 pkgconfig_2.0.3 GlobalOptions_0.1.3