Title: | Detection of 2'-O methylations by RiboMethSeq |
---|---|
Description: | RNAmodR.RiboMethSeq implements the detection of 2'-O methylations on RNA from experimental data generated with the RiboMethSeq protocol. The package builds on the core functionality of the RNAmodR package to detect specific patterns of the modifications in high throughput sequencing data. |
Authors: | Felix G.M. Ernst [aut, cre] , Denis L.J. Lafontaine [ctb, fnd] |
Maintainer: | Felix G.M. Ernst <[email protected]> |
License: | Artistic-2.0 |
Version: | 1.21.0 |
Built: | 2024-10-31 04:35:24 UTC |
Source: | https://github.com/bioc/RNAmodR.RiboMethSeq |
Among the various post-transcriptional RNA modifications, 2'-O methylations are quite common in rRNA and tRNA. They confere resistance to alkaline degradation by preventing a nucleophilic attack on the 3'-phosphate especially in flexible RNA, which is fascilitated by high pH conditions. This property can be queried using a method called RiboMethSeq (Birkedahl et al. 2015, Marchand et al. 2017) for which RNA is treated in alkaline conditions and RNA fragments are used to prepare a sequencing library.
At position containing a 2'-O methylations, read ends are less frequent, which is used to detect and score the2'-O methylations.
dataType
is "ProtectedEndSequenceData"
:
The ModRiboMethSeq
class uses the the
ProtectedEndSequenceData
class to store and aggregate data along the transcripts. The calculated
scores follow the nomenclature of Birkedahl et al. (2015) with the names
scoreRMS
(default), scoreA
, scoreB
and scoreMean
.
The ScoreMax as described by Marchand et al. (2017) are not implemented, yet, since an unambigeous description is not available from the literature.
The ScoreMean as described by Galvanin et al. (2018) is implemented. However, use with caution, since the description is not unambigeous. Currently it is calculated as as: 1 - (n / mean(areaL + areaR)). (n: counts at position, areaL: counts from x position upstream, areaR: counts from x position downstream)
Only samples named treated
are used for this analysis. Normalization
to untreated samples is currently not used.
The ModRiboMethSeq5
class can be used as well. However, as
SequenceData
the
End5SequenceData
is employed using
only the 5'-end positions of reads.
ModRiboMethSeq(x, annotation = NA, sequences = NA, seqinfo = NA, ...) ModSetRiboMethSeq(x, annotation = NA, sequences = NA, seqinfo = NA, ...)
ModRiboMethSeq(x, annotation = NA, sequences = NA, seqinfo = NA, ...) ModSetRiboMethSeq(x, annotation = NA, sequences = NA, seqinfo = NA, ...)
x |
the input which can be of the different types depending on whether
a |
annotation |
annotation data, which must match the information contained
in the BAM files. This is parameter is only required if |
sequences |
sequences matching the target sequences the reads were
mapped onto. This must match the information contained in the BAM files. This
is parameter is only required if |
seqinfo |
An optional |
... |
Optional arguments overwriting default values, which are
To disable minimal values for modification calling, set them to |
a ModRiboMethSeq
or ModSetRiboMethSeq
object
Felix G.M. Ernst [aut]
- Birkedal U, Christensen-Dalsgaard M, Krogh N, Sabarinathan R, Gorodkin J, Nielsen H (2015): "Profiling of ribose methylations in RNA by high-throughput sequencing." Angewandte Chemie (International ed. in English) 54 (2), P. 451–455. DOI: 10.1002/anie.201408362.
- Marchand V, Ayadi L, El Hajj A, Blanloeil-Oillo F, Helm M, Motorin Y (2017): "High-Throughput Mapping of 2'-O-Me Residues in RNA Using Next-Generation Sequencing (Illumina RiboMethSeq Protocol)." Methods in molecular biology (Clifton, N.J.) 1562, P. 171–187. DOI: 10.1007/978-1-4939-6807-7_12.
- Galvanin A, Ayadi L, Helm M, Motorin Y, Marchand V (2017): "Mapping and Quantification of tRNA 2'-O-Methylation by RiboMethSeq". Wajapeyee N., Gupta R. (eds) Epitranscriptomics. Methods in Molecular Biology (Humana Press, New York, NY) 1870, P. 273-295. DOI: 10.1007/978-1-4939-8808-2_21
library(RNAmodR.Data) library(rtracklayer) annotation <- GFF3File(RNAmodR.Data.example.RMS.gff3()) sequences <- RNAmodR.Data.example.RMS.fasta() files <- list("Sample1" = c(treated = RNAmodR.Data.example.RMS.1()), "Sample2" = c(treated = RNAmodR.Data.example.RMS.1())) # Creating a Modifier object of type ModRiboMethSeq mrms <- ModRiboMethSeq(files[[1]], annotation = annotation, sequences = sequences) # Creating a ModifierSet object of type ModSetRiboMethSeq msrms <- ModSetRiboMethSeq(files, annotation = annotation, sequences = sequences)
library(RNAmodR.Data) library(rtracklayer) annotation <- GFF3File(RNAmodR.Data.example.RMS.gff3()) sequences <- RNAmodR.Data.example.RMS.fasta() files <- list("Sample1" = c(treated = RNAmodR.Data.example.RMS.1()), "Sample2" = c(treated = RNAmodR.Data.example.RMS.1())) # Creating a Modifier object of type ModRiboMethSeq mrms <- ModRiboMethSeq(files[[1]], annotation = annotation, sequences = sequences) # Creating a ModifierSet object of type ModSetRiboMethSeq msrms <- ModSetRiboMethSeq(files, annotation = annotation, sequences = sequences)
All of the functions of Modifier
and
the ModifierSet
classes are
inherited by the ModRiboMethSeq
and ModSetRiboMethSeq
classes.
## S4 replacement method for signature 'ModRiboMethSeq' settings(x) <- value ## S4 method for signature 'ModRiboMethSeq' aggregateData(x) ## S4 method for signature 'ModRiboMethSeq' findMod(x) ## S4 method for signature 'ModRiboMethSeq' getDataTrack(x, name, type, ...) ## S4 method for signature 'ModRiboMethSeq,GRanges' plotDataByCoord( x, coord, type = c("ends", "scoreA", "scoreB", "scoreRMS", "scoreMean"), window.size = 15L, ... ) ## S4 method for signature 'ModRiboMethSeq' plotData( x, name, from = 1L, to = 30L, type = c("ends", "scoreA", "scoreB", "scoreRMS", "scoreMean"), ... ) ## S4 method for signature 'ModSetRiboMethSeq,GRanges' plotDataByCoord( x, coord, type = c("scoreRMS", "ends", "scoreA", "scoreB", "scoreMean"), window.size = 15L, ... ) ## S4 method for signature 'ModSetRiboMethSeq' plotData( x, name, from = 1L, to = 30L, type = c("scoreRMS", "ends", "scoreA", "scoreB", "scoreMean"), ... )
## S4 replacement method for signature 'ModRiboMethSeq' settings(x) <- value ## S4 method for signature 'ModRiboMethSeq' aggregateData(x) ## S4 method for signature 'ModRiboMethSeq' findMod(x) ## S4 method for signature 'ModRiboMethSeq' getDataTrack(x, name, type, ...) ## S4 method for signature 'ModRiboMethSeq,GRanges' plotDataByCoord( x, coord, type = c("ends", "scoreA", "scoreB", "scoreRMS", "scoreMean"), window.size = 15L, ... ) ## S4 method for signature 'ModRiboMethSeq' plotData( x, name, from = 1L, to = 30L, type = c("ends", "scoreA", "scoreB", "scoreRMS", "scoreMean"), ... ) ## S4 method for signature 'ModSetRiboMethSeq,GRanges' plotDataByCoord( x, coord, type = c("scoreRMS", "ends", "scoreA", "scoreB", "scoreMean"), window.size = 15L, ... ) ## S4 method for signature 'ModSetRiboMethSeq' plotData( x, name, from = 1L, to = 30L, type = c("scoreRMS", "ends", "scoreA", "scoreB", "scoreMean"), ... )
x |
a |
value |
See |
coord , name , from , to , type , window.size , ...
|
See
|
ModRiboMethSeq
specific arguments for
plotData
:
colour
- a named character vector of length = 4
for the colours of the individual histograms. The names are expected to be
c("ends","scoreA","scoreB","scoreRMS","scoreMean")
settings
See
settings
.
aggregate
See aggregate
.
modify
See modify
.
getDataTrack
a list of
DataTrack
object.
plotData
See
plotDataByCoord
.
plotDataByCoord
See
plotDataByCoord
.
data(msrms,package="RNAmodR.RiboMethSeq") mrms <- msrms[[1]] settings(mrms) aggregate(mrms) modify(mrms) getDataTrack(mrms, "1", mainScore(mrms))
data(msrms,package="RNAmodR.RiboMethSeq") mrms <- msrms[[1]] settings(mrms) aggregate(mrms) modify(mrms) getDataTrack(mrms, "1", mainScore(mrms))
‘RNAmodR.RiboMethSeq' implements the detection of 2’-O methylations from RiboMethSeq data using the workflow and class the package 'RNAmodR' provides.
Felix G M Ernst [aut], Denis L J Lafontaine [fnd]
Further details are described in the man pages of the
Modifier
object and the vignettes.
This contains an example ModifierSet object of type ModSetRiboMethSeq
data(msrms)
data(msrms)
a ModSetRiboMethSeq
instance