Example of importing tRNAdb output as GRanges
tRNA 1.22.0
The tRNA
package provides access to tRNA feature information for subsetting
and visualization. Visualization functions are implemented to compare feature
parameters of multiple tRNA sets and to correlate them to additional data.
As input the package expects a GRanges
object with certain metadata columns.
The following columns are required: tRNA_length
, tRNA_type
,
tRNA_anticodon
, tRNA_seq
, tRNA_str
, tRNA_CCA.end
. The tRNA_str
column
must contain a valid dot bracket annotation. For more details please have a look
at the vignette of the Structstrings
package.
To work with the tRNA
package, tRNA information can be retrieved or loaded
into a R session in a number of ways:
GRanges
object can be constructed manually containing the required
colums mentioned above.import.tRNAscanAsGRanges()
from the tRNAscanImport
packageimport.tRNAdb()
from the tRNAdbImport
packageFor the examples in this vignette a number of predefined GRanges
objects are
loaded.
library(tRNA)
library(Structstrings)
data("gr", package = "tRNA")
To retrieve the sequences for individual tRNA structure elements the functions
gettRNAstructureGRanges
or gettRNAstructureSeqs
can be used. Several
optional arguments can be used to modify the result (See
?gettRNAstructureSeqs
).
# just get the coordinates of the anticodonloop
gettRNAstructureGRanges(gr, structure = "anticodonLoop")
## $anticodonLoop
## IRanges object with 299 ranges and 0 metadata columns:
## start end width
## <integer> <integer> <integer>
## TGG 31 37 7
## TGC 32 38 7
## CAA 31 37 7
## AGA 31 37 7
## TAA 31 37 7
## ... ... ... ...
## CAT 32 38 7
## GAA 31 37 7
## TTA 31 37 7
## TAC 32 38 7
## CAT 32 38 7
gettRNAstructureSeqs(gr, joinFeatures = TRUE, structure = "anticodonLoop")
## $anticodonLoop
## RNAStringSet object of length 299:
## width seq names
## [1] 7 UUUGGGU TGG
## [2] 7 CUUGCAA TGC
## [3] 7 UUCAAGC CAA
## [4] 7 UUAGAAA AGA
## [5] 7 CUUAAGA TAA
## ... ... ...
## [295] 7 CUCAUAA CAT
## [296] 7 UUGAAGA GAA
## [297] 7 UUUUAGU TTA
## [298] 7 UUUACAC TAC
## [299] 7 GUCAUGA CAT
In addition, the sequences can be returned already joined to get a fully blank
padded set of sequences. The boundaries of the individual structures is returned
as metadata of the RNAStringSet
object.
seqs <- gettRNAstructureSeqs(gr[1L:10L], joinCompletely = TRUE)
seqs
## RNAStringSet object of length 10:
## width seq
## [1] 85 GGGCGUGUGGUC-UAGU-GGUAU-GAUUCUCGC...------GCCUGGGUUCAAUUCCCAGCUCGCCCC
## [2] 85 GGGCACAUGGCGCAGUU-GGU-AGCGCGCUUCC...------GCAUCGGUUCGAUUCCGGUUGCGUCCA
## [3] 85 GGUUGUUUGGCC-GAGC-GGUAA-GGCGCCUGA...AA-GAUGCAAGAGUUCGAAUCUCUUAGCAACCA
## [4] 85 GGCAACUUGGCC-GAGU-GGUAA-GGCGAAAGA...U-GCCCGCGCAGGUUCGAGUCCUGCAGUUGUCG
## [5] 85 GGAGGGUUGGCC-GAGU-GGUAA-GGCGGCAGA...UUGUCCGCGCGAGUUCGAACCUCGCAUCCUUCA
## [6] 85 GCGGAUUUAGCUCAGUU-GGG-AGAGCGCCAGA...------GCCUGUGUUCGAUCCACAGAAUUCGCA
## [7] 85 GGUCUCUUGGCC-CAGUUGGUAA-GGCACCGUG...------ACAGCGGUUCGAUCCCGCUAGAGACCA
## [8] 85 GCGCAAGUGGUUUAGU--GGU-AAAAUCCAACG...-------CCCCGGUUCGAUUCCGGGCUUGCGCA
## [9] 85 GGCAACUUGGCC-GAGU-GGUAA-GGCGAAAGA...U-GCCCGCGCAGGUUCGAGUCCUGCAGUUGUCG
## [10] 85 GCUUCUAUGGCC-AAGUUGGUAA-GGCGCCACA...------ACAUCGGUUCAAAUCCGAUUGGAAGCA
# getting the tRNA structure boundaries
metadata(seqs)[["tRNA_structures"]]
## IRanges object with 15 ranges and 0 metadata columns:
## start end width
## <integer> <integer> <integer>
## acceptorStem.prime5 1 7 7
## Dprime5 8 9 2
## DStem.prime5 10 13 4
## Dloop 14 23 10
## DStem.prime3 24 27 4
## ... ... ... ...
## TStem.prime5 61 65 5
## Tloop 66 72 7
## TStem.prime3 73 77 5
## acceptorStem.prime3 78 84 7
## discriminator 85 85 1
Be aware, that gettRNAstructureGRanges
and gettRNAstructureSeqs
might not be
working as expected, if the tRNA sequences in questions are armless or deviate
drastically from the canonical tRNA model. The functions in the tRNA
packages
were thouroughly tested using human mitochondrial tRNA and other tRNAs missing
certain features. However, for fringe cases results may differ. If you encounter
such a case, please report it with an example.
Structure information of the tRNA can be queried for subsetting using several
functions. For the following examples the functions hasAccpeptorStem
and
hasDloop
are used.
gr[hasAcceptorStem(gr, unpaired = TRUE)]
# mismatches and bulged are subsets of unpaired
gr[hasAcceptorStem(gr, mismatches = TRUE)]
gr[hasAcceptorStem(gr, bulged = TRUE)]
# combination of different structure parameters
gr[hasAcceptorStem(gr, mismatches = TRUE) &
hasDloop(gr, length = 8L)]
Please have a look at the man page ?hasAccpeptorStem
for all available
subsetting functions.
To get an overview of tRNA features and compare different datasets, the function
gettRNAFeaturePlots
is used. It accepts a named GRangesList
as input.
Internally it will calculate a list of features values based on the functions
mentioned above and the data contained in the mcols of the GRanges
objects.
# load tRNA data for E. coli and H. sapiens
data("gr_eco", package = "tRNA")
data("gr_human", package = "tRNA")
# get summary plots
grl <- GRangesList(Sce = gr,
Hsa = gr_human,
Eco = gr_eco)
plots <- gettRNAFeaturePlots(grl)
plots$length
plots$tRNAscan_score
plots$gc
plots$tRNAscan_intron
plots$variableLoop_length
To access the results without generating plots, use the function
gettRNASummary
.
To check whether features correlate with additional scores, optional arguments
can be added to gettRNAFeaturePlots
or used from the score
column of the
GRanges
objects. For the first case a list of scores with the same dimensions
as the GRangesList
object has to be provided as the argument scores
. For the
latter case, just set the argument plotScore = TRUE
.
# score column will be used
plots <- gettRNAFeaturePlots(grl, plotScores = TRUE)
plots <- gettRNAFeaturePlots(grl,
scores = list(runif(length(grl[[1L]]),0L,100L),
runif(length(grl[[2L]]),0L,100L),
runif(length(grl[[3L]]),0L,100L)))
plots$length
plots$variableLoop_length
Since all plots returned by the functions mentioned above are ggplot2
objects,
they can be modified manually and changed to suit your needs.
plots$length$layers <- plots$length$layers[c(-1L,-2L)]
plots$length + ggplot2::geom_boxplot()
In addition, the data of the plots can be accessed directly.
head(plots$length$data)
The colours of the plots can be customized directly on creation with the following options.
options("tRNA_colour_palette")
## $tRNA_colour_palette
## [1] "Set1"
options("tRNA_colour_yes")
## $tRNA_colour_yes
## [1] "green"
options("tRNA_colour_no")
## $tRNA_colour_no
## [1] "red"
To retrieve detailed information on the base pairing the function
gettRNABasePairing()
is used. Internally this will construct a
DotBracketStringSet
from the tRNA_str
column, if this column does not
already contain a DotBracketStringSet
. It is then passed on to the
Structstrings::getBasePairing
function.
A valid DotBracket annotation is expected to contain only pairs of <>{}[]()
and the .
character (Please note the orientation. For <>
the orientation is
variable, since the tRNAscan files use the ><
annotation by default. However
upon creation of a DotBracketStringSet
this annotation will be converted).
head(gettRNABasePairing(gr)[[1L]])
## DotBracketDataFrame with 6 rows and 4 columns
## pos forward reverse character
## <integer> <integer> <integer> <character>
## 1 1 1 70 <
## 2 2 2 69 <
## 3 3 3 68 <
## 4 4 4 67 <
## 5 5 5 66 <
## 6 6 0 0 .
head(getBasePairing(gr[1L]$tRNA_str)[[1L]])
## DotBracketDataFrame with 6 rows and 4 columns
## pos forward reverse character
## <integer> <integer> <integer> <character>
## 1 1 1 70 <
## 2 2 2 69 <
## 3 3 3 68 <
## 4 4 4 67 <
## 5 5 5 66 <
## 6 6 0 0 .
The loop ids for the structure elements can be retrieved with the
gettRNALoopIDs()
function, which relies on the Structstrings::getLoopIndices
function. (For more details, please have a look at the ?getLoopIndices
)
gettRNALoopIDs(gr)[[1L]]
## [1] 1 2 3 4 5 5 6 6 6 7 8 9 9 9 9 9 9 9 9 9 9 9 8 7 6
## [26] 10 11 12 13 14 14 14 14 14 14 14 14 14 13 12 11 10 6 6 6 6 15 16 17 18
## [51] 19 19 19 19 19 19 19 19 19 18 17 16 15 6 5 5 4 3 2 1 0
getLoopIndices(gr[1L]$tRNA_str)
## LoopIndexList of length 1
## [[""]] 1 2 3 4 5 5 6 6 6 7 8 9 9 9 9 9 ... 19 19 19 18 17 16 15 6 5 5 4 3 2 1 0
sessionInfo()
## R version 4.4.0 beta (2024-04-15 r86425)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.19-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] 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
## [8] base
##
## other attached packages:
## [1] tRNA_1.22.0 Structstrings_1.20.0 Biostrings_2.72.0
## [4] XVector_0.44.0 GenomicRanges_1.56.0 GenomeInfoDb_1.40.0
## [7] IRanges_2.38.0 S4Vectors_0.42.0 BiocGenerics_0.50.0
## [10] BiocStyle_2.32.0
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.9 utf8_1.2.4 generics_0.1.3
## [4] stringi_1.8.3 digest_0.6.35 magrittr_2.0.3
## [7] RColorBrewer_1.1-3 evaluate_0.23 grid_4.4.0
## [10] bookdown_0.39 fastmap_1.1.1 jsonlite_1.8.8
## [13] tinytex_0.50 BiocManager_1.30.22 httr_1.4.7
## [16] fansi_1.0.6 UCSC.utils_1.0.0 scales_1.3.0
## [19] jquerylib_0.1.4 cli_3.6.2 rlang_1.1.3
## [22] crayon_1.5.2 munsell_0.5.1 withr_3.0.0
## [25] cachem_1.0.8 yaml_2.3.8 tools_4.4.0
## [28] dplyr_1.1.4 colorspace_2.1-0 ggplot2_3.5.1
## [31] GenomeInfoDbData_1.2.12 vctrs_0.6.5 R6_2.5.1
## [34] magick_2.8.3 lifecycle_1.0.4 zlibbioc_1.50.0
## [37] stringr_1.5.1 Modstrings_1.20.0 pkgconfig_2.0.3
## [40] bslib_0.7.0 pillar_1.9.0 gtable_0.3.5
## [43] Rcpp_1.0.12 glue_1.7.0 highr_0.10
## [46] xfun_0.43 tibble_3.2.1 tidyselect_1.2.1
## [49] knitr_1.46 farver_2.1.1 htmltools_0.5.8.1
## [52] rmarkdown_2.26 labeling_0.4.3 compiler_4.4.0