Package 'GeneStructureTools'

Title: Tools for spliced gene structure manipulation and analysis
Description: GeneStructureTools can be used to create in silico alternative splicing events, and analyse potential effects this has on functional gene products.
Authors: Beth Signal
Maintainer: Beth Signal <[email protected]>
License: BSD_3_clause + file LICENSE
Version: 1.27.0
Built: 2024-11-14 05:50:26 UTC
Source: https://github.com/bioc/GeneStructureTools

Help Index

Change transcript biotypes to a broader set

Description

Change transcript biotypes to a broader set in a GRanges GTF object

Usage

addBroadTypes(gtf)

Arguments

gtf

GRanges object of the GTF

Value

GRanges object of the GTF with new transcript types

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, exonsToTranscripts, filterGtfOverlap, removeDuplicateTranscripts, removeSameExon, reorderExonNumbers

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
gtf <- rtracklayer::import(gtfFile)
gtf <- addBroadTypes(gtf)

Add a retained intron to the transcripts it is skipped by

Description

Add a retained intron to the transcripts it is skipped by

Usage

addIntronInTranscript(flankingExons, exons, whippetDataSet = NULL,
  match = "exact", glueExons = TRUE)

Arguments

flankingExons

data.frame generataed by findIntronContainingTranscripts()
exons

GRanges object made from a GTF with ONLY exon annotations (no gene, transcript, CDS etc.)
whippetDataSet

whippetDataSet generated from readWhippetDataSet()
match

what type of match replacement should be done? exact: exact matches to the intron only retain: keep non-exact intron match coordinates in spliced sets, and retain them in retained sets replace: replace non-exact intron match coordinates with event coordinates in spliced sets, and retain in retained sets
glueExons

Join together exons that are not seperated by introns?

Value

GRanges with transcripts containing retained introns

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: findExonContainingTranscripts, findIntronContainingTranscripts, findJunctionPairs, replaceJunction, skipExonInTranscript

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.intronRetention <- filterWhippetEvents(wds, eventTypes="RI")
exons.intronRetention <- findIntronContainingTranscripts(wds.intronRetention, exons)
IntronRetentionTranscripts <- addIntronInTranscript(exons.intronRetention, exons,
whippetDataSet=wds.intronRetention)

exonsFromGRanges <- exons[exons$transcript_id=="ENSMUST00000139129.8" &
exons$exon_number %in% c(3,4)]
intronFromGRanges <- exonsFromGRanges[1]
GenomicRanges::start(intronFromGRanges) <-
GenomicRanges::end(exonsFromGRanges[exonsFromGRanges$exon_number==3])
GenomicRanges::end(intronFromGRanges) <-
GenomicRanges::start(exonsFromGRanges[exonsFromGRanges$exon_number==4])
exons.intronRetention <- findIntronContainingTranscripts(intronFromGRanges, exons)

IntronRetentionTranscripts <-
addIntronInTranscript(exons.intronRetention, exons, match="retain")

Create transcripts with alternative intron usage

Description

Creates transcript isoforms from alternative intron usage tested by leafcutter

Usage

alternativeIntronUsage(altIntronLocs, exons)

Arguments

altIntronLocs

data.frame containing information from the per_intron_results.tab file output from leafcutter. Note that only one cluster of alternative introns can be processed at a time.
exons

GRanges object made from a GTF with ONLY exon annotations (no gene, transcript, CDS etc.)

Value

GRanges object with all potential alternative isoforms skipping the introns specified in either the upregulated or downregulated locations

Author(s)

Beth Signal

Examples

leafcutterFiles <- list.files(system.file("extdata","leafcutter/",
package = "GeneStructureTools"), full.names = TRUE)
leafcutterIntrons <- read.delim(leafcutterFiles[grep("intron_results",
leafcutterFiles)],stringsAsFactors=FALSE)
gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
# single cluster processing
cluster <- leafcutterIntrons[leafcutterIntrons$cluster=="chr16:clu_1396",]
altIsoforms1396 <- alternativeIntronUsage(cluster, exons)
unique(altIsoforms1396$transcript_id)
cluster <- leafcutterIntrons[leafcutterIntrons$cluster=="chr16:clu_1395",]
altIsoforms1395 <- alternativeIntronUsage(cluster, exons)
unique(altIsoforms1395$transcript_id)
# multiple cluster processing
altIsoforms1396plus1395 <- alternativeIntronUsage(cluster, c(exons, altIsoforms1396))
unique(altIsoforms1396plus1395$transcript_id)

Annotate a GRanges gene model with ORF boundries for visualisation with Gviz

Description

Annotate a GRanges gene model with ORF boundries for visualisation with Gviz

Usage

annotateGeneModel(transcripts, orfs)

Arguments

transcripts

GRanges of gene model to be visualised
orfs

ORF predictions. Created by getORFs()

Value

data.frame of a gene model for visualisation

Author(s)

Beth Signal

See Also

Other Gviz gene structure visualisation: makeGeneModel

Examples

gtf <- rtracklayer::import(system.file("extdata", "example_gtf.gtf",
package="GeneStructureTools"))
transcript <- gtf[gtf$type=="exon" & gtf$gene_name=="Neurl1a"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
# longest ORF for each transcripts
orfs <- getOrfs(transcript, BSgenome = g, returnLongestOnly = TRUE)
geneModelAnnotated <- annotateGeneModel(transcript, orfs)

Evaluate the change in an attribute between a set of 'normal' transcripts and 'alternative' transcripts

Description

Evaluate the change in an attribute between a set of 'normal' transcripts and 'alternative' transcripts

Usage

attrChangeAltSpliced(orfsX, orfsY, attribute = "orf_length",
  compareBy = "gene", useMax = TRUE, compareUTR = FALSE)

Arguments

orfsX

orf information for 'normal' transcripts. Generated by getOrfs()
orfsY

orf information for 'alternative' transcripts. Generated by getOrfs()
attribute

attribute to compare
compareBy

compare by 'transcript' isoforms or by 'gene' groups
useMax

use max as the summary function when multiple isoforms are aggregated? If FALSE, will use min instead.
compareUTR

compare the UTR lengths between transcripts? Only runs if attribute = "orf_length"

Value

data.frame with attribute changes

Author(s)

Beth Signal

See Also

Other transcript isoform comparisons: orfDiff, transcriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.exonSkip <- filterWhippetEvents(wds, eventTypes="CE",psiDelta = 0.2)
exons.exonSkip <- findExonContainingTranscripts(wds.exonSkip, exons,
variableWidth=0, findIntrons=FALSE, transcripts)
ExonSkippingTranscripts <- skipExonInTranscript(exons.exonSkip, exons, whippetDataSet=wds.exonSkip)

orfsSkipped <- getOrfs(ExonSkippingTranscripts[ExonSkippingTranscripts$set=="skipped_exon"],
BSgenome = g)
orfsIncluded <- getOrfs(ExonSkippingTranscripts[ExonSkippingTranscripts$set=="included_exon"],
BSgenome = g)
attrChangeAltSpliced(orfsSkipped, orfsIncluded,attribute = "orf_length")

Method coordinates

Description

Method coordinates

Usage

coordinates(whippetDataSet)

## S4 method for signature 'whippetDataSet'
coordinates(whippetDataSet)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()

Value

whippet splicing event coordinates as a GRanges object

See Also

Other whippet data processing: diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)

coordinates <- coordinates(wds)

Convert DEXSeq ids to gene ids

Description

Convert DEXSeq ids to gene ids

Usage

DEXSeqIdsToGeneIds(DEXSeqIds, removeVersion = FALSE, containsE = TRUE)

Arguments

DEXSeqIds

vector of DEXSeq group or exon ids
removeVersion

remove the version (.xx) of the gene?
containsE

do the DEXSeq exons ids contain :E00X?

Value

vector of unique gene ids

Author(s)

Beth Signal

See Also

Other DEXSeq processing methods: findDEXexonType, summariseExonTypes

Examples

# multiple genes in name
DEXSeqId <- "ENSMUSG00000027618.17+ENSMUSG00000098950.7+ENSMUSG00000089824.10+ENSMUSG00000074643.12"
DEXSeqIdsToGeneIds(DEXSeqId)

# exonic part number in id
DEXSeqIdsToGeneIds("ENSMUSG00000001017.15:E013", removeVersion=TRUE)

Method diffSplicingResults

Description

Method diffSplicingResults

Usage

diffSplicingResults(whippetDataSet)

## S4 method for signature 'whippetDataSet'
diffSplicingResults(whippetDataSet)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()

Value

differential splicing results data.frame (originally from a whippet .diff file)

See Also

Other whippet data processing: coordinates, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)

diffSplicingResults <- diffSplicingResults(wds)

Convert an exon-level gtf annotation to a transcript-level gtf annotation

Description

Convert an exon-level gtf annotation to a transcript-level gtf annotation

Usage

exonsToTranscripts(exons)

Arguments

exons

GRanges object with exons

Value

GRanges object with transcripts

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, addBroadTypes, filterGtfOverlap, removeDuplicateTranscripts, removeSameExon, reorderExonNumbers

Examples

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon" & gtf$transcript_id=="ENSMUST00000126412.1"]
exons
transcripts <- exonsToTranscripts(exons)
transcripts

Filter a GTF overlap to remove exons when exon is annotated as a CDS/UTR

Description

Filter a GTF overlap to remove exons when exon is annotated as a CDS/UTR

Usage

filterGtfOverlap(gtf.from)

Arguments

gtf.from

GRanges object of the GTF produced from an overlap

Value

GRanges object of the GTF with redundant exons removed

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, addBroadTypes, exonsToTranscripts, removeDuplicateTranscripts, removeSameExon, reorderExonNumbers

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
gtf <- rtracklayer::import(gtfFile)
overlap <- as.data.frame(GenomicRanges::findOverlaps(gtf[which(gtf$type=="CDS")[1]], gtf))
table(gtf$type[overlap$subjectHits])
overlapFiltered <- filterGtfOverlap(gtf[overlap$subjectHits])
table(overlapFiltered$type[overlap$subjectHits])
overlap <- as.data.frame(GenomicRanges::findOverlaps(gtf[which(
gtf$transcript_type=="retained_intron")[1]],gtf))
table(gtf$type[overlap$subjectHits])
overlapFiltered <- filterGtfOverlap(gtf[overlap$subjectHits])
table(overlapFiltered$type[overlap$subjectHits])

Filter out significant events from a whippet diff comparison

Description

Filter out significant events from a whippet diff comparison

Usage

filterWhippetEvents(whippetDataSet, probability = 0.95, psiDelta = 0.1,
  eventTypes = "all", idList = NA, minCounts = NA, medianCounts = NA,
  sampleTable)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()
probability

minimum probability required to call event as significant
psiDelta

minimum change in psi required to call an event as significant
eventTypes

which event type to filter for? default = "all"
idList

(optional) list of gene ids to filter for
minCounts

minumum number of counts for all replicates in at least one condition to call an event as significant
medianCounts

median count for all replicates in at least one condition to call an event as significant
sampleTable

data.frame with sample names and conditions. Only needed if filtering with counts.

Value

filtered whippet differential comparison data.frame

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

Find a DEXSeq exons' biotype

Description

Find a DEXSeq exons' biotype

Usage

findDEXexonType(DEXSeqExonId, DEXSeqGtf, gtf, set = "overlap")

Arguments

DEXSeqExonId

vector of DEXSeq exon ids
DEXSeqGtf

GRanges object of the DEXSeq formatted gtf
gtf

GRanges object of the GTF annotated with exon biotypes - i.e. exon, CDS, UTR
set

which overlapping set of exon biotypes to return - to, from, and/or overlap

Value

overlaping types

Author(s)

Beth Signal

See Also

Other DEXSeq processing methods: DEXSeqIdsToGeneIds, summariseExonTypes

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
DEXSeqGtfFile <- system.file("extdata","gencode.vM14.dexseq.gtf",
package = "GeneStructureTools")

gtf <- rtracklayer::import(gtfFile)
gtf <- UTR2UTR53(gtf)
DEXSeqGtf <- rtracklayer::import(DEXSeqGtfFile)

findDEXexonType("ENSMUSG00000032366.15:E028", DEXSeqGtf, gtf)

DEXSeqResultsFile <- system.file("extdata","dexseq_results_significant.txt",
package = "GeneStructureTools")
DEXSeqResults <- read.table(DEXSeqResultsFile, sep="\t")

findDEXexonType(rownames(DEXSeqResults), DEXSeqGtf, gtf)

Given the location of a whole spliced in exon, find transcripts which can splice out this exon

Description

Given the location of a whole spliced in exon, find transcripts which can splice out this exon

Usage

findExonContainingTranscripts(input, exons, variableWidth = 0,
  findIntrons = FALSE, transcripts)

Arguments

input

whippetDataSet generated from readWhippetDataSet() or a Granges of exon coordinates
exons

GRanges object made from a GTF containing exon coordinates
variableWidth

How many nts overhang is allowed for finding matching exons (default = 0, i.e. complete match)
findIntrons

Find transcripts where the event occurs within the intron?
transcripts

GRanges object made from a GTF containing transcript coordinates (only required if findIntrons=TRUE)

Value

data.frame with all overlapping exons

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: addIntronInTranscript, findIntronContainingTranscripts, findJunctionPairs, replaceJunction, skipExonInTranscript

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.exonSkip <- filterWhippetEvents(wds, eventTypes="CE",psiDelta = 0.2)
exons.exonSkip <- findExonContainingTranscripts(wds.exonSkip, exons,
variableWidth=0, findIntrons=FALSE, transcripts)

exonFromGRanges <- exons[exons$exon_id == "ENSMUSE00001271768.1"]
exons.exonSkip <- findExonContainingTranscripts(exonFromGRanges, exons,
variableWidth=0, findIntrons=FALSE, transcripts)

Given the location of a whole retained intron, find transcripts which splice out this intron

Description

Given the location of a whole retained intron, find transcripts which splice out this intron

Usage

findIntronContainingTranscripts(input, exons, match = "exact")

Arguments

input

whippetDataSet generated from readWhippetDataSet() or a Granges of intron coordinates
exons

GRanges object made from a GTF with ONLY exon annotations (no gene, transcript, CDS etc.)
match

what type of matching to perform? exact = only exons which bound the intron exactly, introns = any exon pairs which overlap the intron, all = any exon pairs AND single exons which overlap the intron

Value

data.frame with all flanking exon pairs

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: addIntronInTranscript, findExonContainingTranscripts, findJunctionPairs, replaceJunction, skipExonInTranscript

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.intronRetention <- filterWhippetEvents(wds, eventTypes="RI")
exons.intronRetention <- findIntronContainingTranscripts(input=wds.intronRetention, exons)

exonsFromGRanges <- exons[exons$transcript_id=="ENSMUST00000139129.8" &
exons$exon_number %in% c(3,4)]
intronFromGRanges <- exonsFromGRanges[1]
GenomicRanges::start(intronFromGRanges) <-
GenomicRanges::end(exonsFromGRanges[exonsFromGRanges$exon_number==3])
GenomicRanges::end(intronFromGRanges) <-
GenomicRanges::start(exonsFromGRanges[exonsFromGRanges$exon_number==4])
exons.intronRetention <- findIntronContainingTranscripts(intronFromGRanges, exons)

Find alternative junctions for Whippet alternative splicing events

Description

Find junctions that pair with each end of an AA (alt. acceptor) or AD (alt. donor) whippet range Find junctions that pair with the upsteam/downstream exon of an AF (alt. first exon) or an AL (alt. last exon)

Usage

findJunctionPairs(whippetDataSet, jncCoords, type = NA)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()
jncCoords

GRanges object with Whippet junctions. Generated by readWhippetJNCfiles()
type

type of Whippet event (AA/AD/AF/AL). Note only one event type should be processed at a time.

Value

GRanges object with alternative junctions. Each event should have a set of X (for which the psi measurement is reported) junctions, and alternative Y junctions.

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: addIntronInTranscript, findExonContainingTranscripts, findIntronContainingTranscripts, replaceJunction, skipExonInTranscript

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.altAce <- filterWhippetEvents(wds, eventTypes="AA")
jncPairs.altAce <- findJunctionPairs(wds.altAce, type="AA")

wds.altDon <- filterWhippetEvents(wds, eventTypes="AD")
jncPairs.altDon <- findJunctionPairs(wds.altDon, type="AD")

wds.altFirst <- filterWhippetEvents(wds, eventTypes="AF", psiDelta=0.2)
jncPairs.altFirst <- findJunctionPairs(wds.altFirst, type="AF")

wds.altLast <- filterWhippetEvents(wds, eventTypes="AL", psiDelta=0.2)
jncPairs.altLast <- findJunctionPairs(wds.altLast, type="AL")

Format Whippet co-ordinates as a GRanges object

Description

Format Whippet co-ordinates as a GRanges object

Usage

formatWhippetEvents(whippet)

Arguments

whippet

data.frame containing event location information. May be generated by readWhippetDIFFfiles()

Value

GRanges object with events

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- list.files(system.file("extdata","whippet/",
package = "GeneStructureTools"), full.names = TRUE)
diffFiles <- whippetFiles[grep(".diff", whippetFiles)]
whippetDiffSplice <- readWhippetDIFFfiles(diffFiles)
whippetCoords <- formatWhippetEvents(whippetDiffSplice)

Get open reading frames for transcripts

Description

Get open reading frames for transcripts

Usage

getOrfs(transcripts, BSgenome = NULL, returnLongestOnly = TRUE,
  allFrames = FALSE, longest = 1, exportFasta = FALSE, fastaFile = NULL,
  uORFs = FALSE)

Arguments

transcripts

GRanges object with ONLY exon annotations (no gene, transcript, CDS etc.) with all transcripts for orf retrevial
BSgenome

BSgenome object
returnLongestOnly

only return longest ORF?
allFrames

return longest ORF for all 3 frames?
longest

return x longest ORFs (regardless of frames)
exportFasta

export a .fa.gz file with nucleotide sequences for each transcript?
fastaFile

file name for .fa.gz export
uORFs

get uORF summaries?

Value

data.frame with longest orf details

Author(s)

Beth Signal

See Also

Other ORF annotation: getUOrfs, maxLocation, orfSimilarity

Examples

gtf <- rtracklayer::import(system.file("extdata", "example_gtf.gtf",
package="GeneStructureTools"))
transcript <- gtf[gtf$type=="exon" & gtf$gene_name=="Neurl1a"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
# longest ORF for each transcripts
orfs <- getOrfs(transcript, BSgenome = g, returnLongestOnly = TRUE)
# longest ORF in all 3 frames for each transcript
orfs <- getOrfs(transcript, BSgenome = g, allFrames = TRUE)
# longest 3 ORFS in eacht transcript
orfs <- getOrfs(transcript, BSgenome = g, returnLongestOnly = FALSE, longest=3)

Get upstream open reading frames for transcripts with annotated main ORFs

Description

Get upstream open reading frames for transcripts with annotated main ORFs

Usage

getUOrfs(transcripts, BSgenome = NULL, orfs, findExonB = FALSE)

Arguments

transcripts

GRanges object with ONLY exon annotations (no gene, transcript, CDS etc.) with all transcripts for orf retrevial
BSgenome

BSgenome object
orfs

orf annotation for the transcripts object. Generated by getOrfs(transcripts, ...)
findExonB

find the distance to and exon number of the downstream (B) junction?

Value

data.frame with all upstream ORF details.

Author(s)

Beth Signal

See Also

Other ORF annotation: getOrfs, maxLocation, orfSimilarity

Examples

gtf <- rtracklayer::import(system.file("extdata", "example_gtf.gtf",
package="GeneStructureTools"))
transcript <- gtf[gtf$type=="exon" & gtf$gene_name=="Neurl1a"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
# longest ORF for each transcripts
orfs <- getOrfs(transcript, BSgenome = g, returnLongestOnly = FALSE)
uORFS <- getUOrfs(transcript, BSgenome = g, orfs = orfs, findExonB = TRUE)

Method junctions

Description

Method junctions

Usage

junctions(whippetDataSet)

## S4 method for signature 'whippetDataSet'
junctions(whippetDataSet)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()

Value

junctions GRanges object (originally from a whippet .jnc file)

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)

junctions <- junctions(wds)

Compare open reading frames for whippet differentially spliced events

Description

Compare open reading frames for whippet differentially spliced events

Usage

leafcutterTranscriptChangeSummary(significantEvents,
  combineGeneEvents = FALSE, exons, BSgenome, NMD = FALSE,
  showProgressBar = TRUE, exportGTF = NULL)

Arguments

significantEvents

data.frame containing information from the per_intron_results.tab file output from leafcutter.
combineGeneEvents

combine clusters occuring in the same gene? Currently not reccomended.
exons

GRanges gtf annotation of exons
BSgenome

BSGenome object containing the genome for the species analysed
NMD

Use NMD predictions? (Note: notNMD must be installed to use this feature)
showProgressBar

show a progress bar of alternative isoform generation?
exportGTF

file name to export alternative isoform GTFs (default=NULL)

Value

data.frame containing signficant whippet diff data and ORF change summaries

Author(s)

Beth Signal

Examples

leafcutterFiles <- list.files(system.file("extdata","leafcutter/",
package = "GeneStructureTools"), full.names = TRUE)
leafcutterIntrons <- read.delim(leafcutterFiles[
grep("intron_results", leafcutterFiles)],stringsAsFactors=FALSE)
gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
leafcutterTranscriptChangeSummary(significantEvents = leafcutterIntrons,
exons=exons,BSgenome = g,NMD=FALSE)

Convert GRanges gene model to data.frame for visualisation with Gviz

Description

Convert GRanges gene model to data.frame for visualisation with Gviz

Usage

makeGeneModel(transcript)

Arguments

transcript

GRanges of gene model to be visualised

Value

data.frame of a gene model for visualisation

Author(s)

Beth Signal

See Also

Other Gviz gene structure visualisation: annotateGeneModel

Examples

gtf <- rtracklayer::import(system.file("extdata", "example_gtf.gtf",
package="GeneStructureTools"))
transcript <- gtf[gtf$type=="exon" & gtf$gene_name=="Neurl1a"]
geneModel <- makeGeneModel(transcript)

Find the largest distance between two vectors of numbers Helper function for get_orfs

Description

Find the largest distance between two vectors of numbers Helper function for get_orfs

Usage

maxLocation(startSite, stopSite, longest = 1)

Arguments

startSite

vector of start sites - i.e Met amino acid positions
stopSite

vector of stop sites - i.e Stop (*) amino acid positions
longest

which pair to return (1 = longest pair, 2= 2nd longest pair etc.)

Value

sequential start site and end site with the greatest difference

Author(s)

Beth Signal

See Also

Other ORF annotation: getOrfs, getUOrfs, orfSimilarity

Examples

starts <- c(1,10,15,25)
stops <- c(4,16,50,55)
# longest start site = 25, longest stop site = 50
maxLocation(starts, stops, longest = 1)
starts <- c(1,10,15,25)
stops <- c(4,14,50,55)
# longest start site = 15, longest stop site = 50
maxLocation(starts, stops, longest = 1)
# 2nd longest start site = 10, 2nd longest stop site = 14
maxLocation(starts, stops, longest = 2)

Evaluate changes to ORFs caused by alternative splicing

Description

Evaluate changes to ORFs caused by alternative splicing

Usage

orfDiff(orfsX, orfsY, filterNMD = TRUE, geneSimilarity = TRUE,
  compareUTR = TRUE, compareBy = "gene", allORFs = NULL)

Arguments

orfsX

orf information for 'normal' transcripts. Generated by getOrfs()
orfsY

orf information for 'alternative' transcripts. Generated by getOrfs()
filterNMD

filter orf information for transcripts not targeted by nmd first?
geneSimilarity

compare orf to all orfs in gene?
compareUTR

compare UTRs?
compareBy

compare by 'transcript' isoforms or by 'gene' groups
allORFs

orf information for all transcripts for novel sequence comparisons. Generated by getOrfs()

Value

data.frame with orf changes

Author(s)

Beth Signal

See Also

Other transcript isoform comparisons: attrChangeAltSpliced, transcriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

orfsProteinCoding <- getOrfs(exons[exons$gene_name=="Prex2" &
exons$transcript_type=="protein_coding"], BSgenome = g)
orfsNMD <- getOrfs(exons[exons$gene_name=="Prex2" &
exons$transcript_type=="nonsense_mediated_decay"], BSgenome = g)
orfDiff(orfsProteinCoding, orfsNMD, filterNMD=FALSE)

wds.exonSkip <- filterWhippetEvents(wds, eventTypes="CE",psiDelta = 0.2)
exons.exonSkip <- findExonContainingTranscripts(wds.exonSkip, exons,
variableWidth=0, findIntrons=FALSE, transcripts)
ExonSkippingTranscripts <- skipExonInTranscript(exons.exonSkip, exons, whippetDataSet=wds.exonSkip)

orfsSkipped <- getOrfs(ExonSkippingTranscripts[ExonSkippingTranscripts$set=="skipped_exon"],
BSgenome = g)
orfsIncluded <- getOrfs(ExonSkippingTranscripts[ExonSkippingTranscripts$set=="included_exon"],
BSgenome = g)
orfDiff(orfsSkipped, orfsIncluded, filterNMD=FALSE)

calculate percentage of orfB contained in orfA

Description

calculate percentage of orfB contained in orfA

Usage

orfSimilarity(orfA, orfB, substitutionCost = 100)

Arguments

orfA

character string of ORF amino acid sequence
orfB

character string of ORF amino acid sequence
substitutionCost

cost for substitutions in ORF sequences. Set to 1 if substitutions should be weighted equally to insertions and deletions.

Value

percentage of orfB contained in orfA

Author(s)

Beth Signal

See Also

Other ORF annotation: getOrfs, getUOrfs, maxLocation

Examples

orfSimilarity("MFGLDIYAGTRSSFRQFSLT","MFGLDIYAGTRSSFRQFSLT")
orfSimilarity("MFGLDIYAGTRSSFRQFSLT","MFGLDIYAFRQFSLT")
orfSimilarity("MFGLDIYAFRQFSLT","MFGLDIYAGTRSSFRQFSLT")
orfSimilarity("MFGLDIYAGTRXXFRQFSLT","MFGLDIYAGTRSSFRQFSLT")
orfSimilarity("MFGLDIYAGTRXXFSLT","MFGLDIYAGTRSSFRQFSLT", 1)

Annotate introns and exonic parts by overlaping exon biotype

Description

Annotate introns and exonic parts by overlaping exon biotype

Usage

overlapTypes(queryCoords, gtf, set = c("from", "to", "overlap"))

Arguments

queryCoords

GRanges object of the query regions
gtf

GRanges object of the GTF annotated with exon biotypes - i.e. exon, CDS, UTR
set

which overlapping set of exon biotypes to return - to, from, and/or overlap

Value

overlaping types in a data.frame

Author(s)

Beth Signal

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
DEXSeqGtfFile <- system.file("extdata","gencode.vM14.dexseq.gtf",
package = "GeneStructureTools")

gtf <- rtracklayer::import(gtfFile)
gtf <- UTR2UTR53(gtf)
DEXSeqGtf <- rtracklayer::import(DEXSeqGtfFile)

overlapTypes(DEXSeqGtf[1:10], gtf)

Method readCounts

Description

Method readCounts

Usage

readCounts(whippetDataSet)

## S4 method for signature 'whippetDataSet'
readCounts(whippetDataSet)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()

Value

whippet read count data.frame (originally from a whippet .psi file)

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)

readCounts <- readCounts(wds)

Import whippet results files as a whippetDataSet

Description

Import whippet results files as a whippetDataSet

Usage

readWhippetDataSet(filePath = ".")

Arguments

filePath

path to whippet output files

Value

whippetDataSet

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)

Read in a list of whippet .diff.gz files and format as a data.frame

Description

Read in a list of whippet .diff.gz files and format as a data.frame

Usage

readWhippetDIFFfiles(files)

Arguments

files

vector of *.diff.gz file names

Value

data.frame with junction counts for all files

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- list.files(system.file("extdata","whippet/",
package = "GeneStructureTools"), full.names = TRUE)
diffFiles <- whippetFiles[grep(".diff", whippetFiles)]
whippetDiffSplice <- readWhippetDIFFfiles(diffFiles)

Read in a list of whippet .jnc.gz files and format as a GRanges object

Description

Read in a list of whippet .jnc.gz files and format as a GRanges object

Usage

readWhippetJNCfiles(files)

Arguments

files

vector of *.jnc.gz file names

Value

GRanges object with junctions

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetPSIfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- list.files(system.file("extdata","whippet/",
package = "GeneStructureTools"), full.names = TRUE)
jncFiles <- whippetFiles[grep(".jnc", whippetFiles)]
whippetJNC <- readWhippetJNCfiles(jncFiles)

Read in a list of whippet .psi.gz files and format as a data.frame

Description

Read in a list of whippet .psi.gz files and format as a data.frame

Usage

readWhippetPSIfiles(files, attribute = "Total_Reads", maxNA = NA)

Arguments

files

vector of *.psi.gz file names
attribute

which attribute from the PSI files to use (Total_Reads, Psi, CI_width)
maxNA

maximum number of NA values allowed before a site is removed

Value

data.frame with junction counts for all files

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, whippetTranscriptChangeSummary

Examples

whippetFiles <- list.files(system.file("extdata","whippet/",
package = "GeneStructureTools"), full.names = TRUE)
psiFiles <- whippetFiles[grep(".psi", whippetFiles)]
whippetPSI <- readWhippetPSIfiles(psiFiles)

Remove transcript duplicates

Description

Removes Structural duplicates of transcripts in a GRanges object Note that duplicates must have different transcript ids.

Usage

removeDuplicateTranscripts(transcripts)

Arguments

transcripts

GRanges object with transcript structures in exon form

Value

GRanges object with unique transcript structures in exon form

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, addBroadTypes, exonsToTranscripts, filterGtfOverlap, removeSameExon, reorderExonNumbers

Examples

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
exons.altName <- exons
exons.altName$transcript_id <- paste(exons.altName$transcript_id, "duplicated", sep="_")
exons.duplicated <- c(exons, exons.altName)
length(exons.duplicated)
exons.deduplicated <- removeDuplicateTranscripts(exons.duplicated)
length(exons.deduplicated)

Remove exon duplicates

Description

Removes structural duplicates of exons in a GRanges object

Usage

removeSameExon(exons)

Arguments

exons

GRanges object with exons

Value

GRanges object with unique exons

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, addBroadTypes, exonsToTranscripts, filterGtfOverlap, removeDuplicateTranscripts, reorderExonNumbers

Examples

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
exons.duplicated <- c(exons[1:4], exons[1:4])
length(exons.duplicated)
exons.deduplicated <- removeSameExon(exons.duplicated)
length(exons.deduplicated)

Remove version number from ensembl gene/transcript ids

Description

Remove version number from ensembl gene/transcript ids

Usage

removeVersion(ids)

Arguments

ids

vector of ensembl ids

Value

vector of ensembl ids without the version number

Author(s)

Beth Signal

Examples

removeVersion("ENSMUSG00000001017.15")

Reorder the exon numbers in a gtf annotation

Description

Reorder the exon numbers in a gtf annotation

Usage

reorderExonNumbers(exons, by = "transcript_id")

Arguments

exons

GRanges object made from a GTF with ONLY exon annotations (no gene, transcript, CDS etc.)
by

what column are the transcripts grouped by?

Value

The same input GRanges, but with exon numbers reordered.

Author(s)

Beth Signal

See Also

Other gtf manipulation: UTR2UTR53, addBroadTypes, exonsToTranscripts, filterGtfOverlap, removeDuplicateTranscripts, removeSameExon

Examples

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
exons <- reorderExonNumbers(exons)

Find transcripts containing/overlapping junctions and replace them with alternative junctions

Description

Find transcripts containing/overlapping junctions and replace them with alternative junctions

Usage

replaceJunction(whippetDataSet, junctionPairs, exons, type = NA)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()
junctionPairs

GRanges object with alternative Whippet junctions. Generated by findJunctionPairs()
exons

GRanges object made from a GTF containing exon coordinates
type

type of Whippet event (AA/AD/AF/AL). Note only one event type should be processed at a time.

Value

GRanges object with transcripts containing alternative junctions.

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: addIntronInTranscript, findExonContainingTranscripts, findIntronContainingTranscripts, findJunctionPairs, skipExonInTranscript

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.altAce <- filterWhippetEvents(wds, eventTypes="AA")
jncPairs.altAce <- findJunctionPairs(wds.altAce, type="AA")
transcripts.altAce <- replaceJunction(wds.altAce, jncPairs.altAce, exons, type="AA")

wds.altDon <- filterWhippetEvents(wds, eventTypes="AD")
jncPairs.altDon <- findJunctionPairs(wds.altDon, type="AD")
transcripts.altDon <- replaceJunction(wds.altDon, jncPairs.altDon, exons, type="AD")

wds.altFirst <- filterWhippetEvents(wds, eventTypes="AF", psiDelta=0.2)
jncPairs.altFirst <- findJunctionPairs(wds.altFirst, type="AF")
transcripts.altFirst <- replaceJunction(wds.altFirst, jncPairs.altFirst, exons, type="AF")

wds.altLast <- filterWhippetEvents(wds, eventTypes="AL", psiDelta=0.2)
jncPairs.altLast <- findJunctionPairs(wds.altLast, type="AL")
transcripts.altLast <- replaceJunction(wds.altLast, jncPairs.altLast, exons, type="AL")

Remove and include a skipped exon from the transcripts it overlaps

Description

Remove and include a skipped exon from the transcripts it overlaps

Usage

skipExonInTranscript(skippedExons, exons, glueExons = TRUE,
  whippetDataSet = NULL, match = "exact")

Arguments

skippedExons

data.frame generataed by findExonContainingTranscripts()
exons

GRanges object made from a GTF with ONLY exon annotations (no gene, transcript, CDS etc.)
glueExons

Join together exons that are not seperated by exons?
whippetDataSet

whippetDataSet generated from readWhippetDataSet()
match

what type of match replacement should be done? exact: exact matches to the skipped event only, also removes any intron overlaps skip: keep non-exact exon match coordinates in included sets, and skip them in skipped sets replace: replace non-exact exon match coordinates with event coordinates in included sets, and skip them in skipped sets

Value

GRanges with transcripts skipping exons

Author(s)

Beth Signal

See Also

Other whippet splicing isoform creation: addIntronInTranscript, findExonContainingTranscripts, findIntronContainingTranscripts, findJunctionPairs, replaceJunction

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
transcripts <- gtf[gtf$type=="transcript"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.exonSkip <- filterWhippetEvents(wds, eventTypes="CE",psiDelta = 0.2)
exons.exonSkip <- findExonContainingTranscripts(wds.exonSkip, exons,
variableWidth=0, findIntrons=FALSE, transcripts)
ExonSkippingTranscripts <- skipExonInTranscript(exons.exonSkip, exons, whippetDataSet=wds.exonSkip)

exonFromGRanges <- exons[exons$exon_id == "ENSMUSE00001271768.1"]
exons.exonSkip <- findExonContainingTranscripts(exonFromGRanges, exons,
variableWidth=0, findIntrons=FALSE, transcripts)
ExonSkippingTranscripts <- skipExonInTranscript(exons.exonSkip, exons, match="skip")

Summarise exon biotypes to broader categories

Description

Summarise exon biotypes to broader categories

Usage

summariseExonTypes(types)

Arguments

types

vector of exon biotypes

Value

vector of broader exon biotypes

Author(s)

Beth Signal

See Also

Other DEXSeq processing methods: DEXSeqIdsToGeneIds, findDEXexonType

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
DEXSeqGtfFile <- system.file("extdata","gencode.vM14.dexseq.gtf",
package = "GeneStructureTools")

gtf <- rtracklayer::import(gtfFile)
gtf <- UTR2UTR53(gtf)
DEXSeqGtf <- rtracklayer::import(DEXSeqGtfFile)

findDEXexonType("ENSMUSG00000032366.15:E028", DEXSeqGtf, gtf)

DEXSeqResultsFile <- system.file("extdata","dexseq_results_significant.txt",
package = "GeneStructureTools")
DEXSeqResults <- read.table(DEXSeqResultsFile, sep="\t")

types <- findDEXexonType(rownames(DEXSeqResults), DEXSeqGtf, gtf)
summarisedTypes <- summariseExonTypes(types)
table(types, summarisedTypes)

Compare open reading frames for two sets of paired transcripts

Description

Compare open reading frames for two sets of paired transcripts

Usage

transcriptChangeSummary(transcriptsX, transcriptsY, BSgenome, exons,
  NMD = FALSE, NMDModel = NULL, compareBy = "gene",
  orfPrediction = "allFrames", compareToGene = FALSE,
  whippetDataSet = NULL, exportGTF = NULL)

Arguments

transcriptsX

GRanges object with exon annotations for all transcripts to be compared for the 'normal' condition
transcriptsY

GRanges object with exon annotations for all transcripts to be compared for the 'alternative' condition
BSgenome

BSGenome object containing the genome for the species analysed
exons

GRanges object made from a GTF containing exon coordinates
NMD

Use NMD predictions? (Note: notNMD must be installed to use this feature)
NMDModel

Use the "base" or "lncRNA" NMD model?
compareBy

compare isoforms by 'transcript' id, or aggregate all changes occuring by 'gene'
orfPrediction

What type of orf predictions to return. default= "allFrames"
compareToGene

compare alternative isoforms to all normal gene isoforms (in exons)
whippetDataSet

whippetDataSet generated from readWhippetDataSet() Use if PSI directionality should be taken into account when comparing isoforms.
exportGTF

file name to export alternative isoform GTFs (default=NULL)

Value

Summarised ORF changes data.frame

Author(s)

Beth Signal

See Also

Other transcript isoform comparisons: attrChangeAltSpliced, orfDiff

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
exons <- gtf[gtf$type=="exon"]
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

wds.exonSkip <- filterWhippetEvents(wds, eventTypes="CE",psiDelta = 0.2)

exons.exonSkip <- findExonContainingTranscripts(wds.exonSkip, exons,
variableWidth=0, findIntrons=FALSE, transcripts)
ExonSkippingTranscripts <- skipExonInTranscript(exons.exonSkip, exons, whippetDataSet=wds.exonSkip)
transcriptChangeSummary(ExonSkippingTranscripts[ExonSkippingTranscripts$set=="included_exon"],
ExonSkippingTranscripts[ExonSkippingTranscripts$set=="skipped_exon"],
BSgenome=g,exons)

Annotate UTRs from Gencode GTF as 5' or 3'

Description

Annotate UTRs from Gencode GTF as 5' or 3'

Usage

UTR2UTR53(gtf)

Arguments

gtf

GRanges object of the GTF

Value

gtf annotation GRanges object

Author(s)

Beth Signal

See Also

Other gtf manipulation: addBroadTypes, exonsToTranscripts, filterGtfOverlap, removeDuplicateTranscripts, removeSameExon, reorderExonNumbers

Examples

gtfFile <- system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools")
gtf <- rtracklayer::import(gtfFile)
gtf <- UTR2UTR53(gtf)
table(gtf$type)

Class whippetDataSet

Description

Class whippetDataSet contains information read from whippet output files

Compare open reading frames for whippet differentially spliced events

Description

Compare open reading frames for whippet differentially spliced events

Usage

whippetTranscriptChangeSummary(whippetDataSet, gtf.all = NULL, BSgenome,
  eventTypes = "all", exons = NULL, transcripts = NULL, NMD = FALSE,
  exportGTF = NULL)

Arguments

whippetDataSet

whippetDataSet generated from readWhippetDataSet()
gtf.all

GRanges gtf annotation (can be used instead of specifying exons and transcripts)
BSgenome

BSGenome object containing the genome for the species analysed
eventTypes

which event type to filter for? default = "all"
exons

GRanges gtf annotation of exons
transcripts

GRanges gtf annotation of transcripts
NMD

Use NMD predictions? (Note: notNMD must be installed to use this feature)
exportGTF

file name to export alternative isoform GTFs (default=NULL)

Value

data.frame containing signficant whippet diff data and ORF change summaries

Author(s)

Beth Signal

See Also

Other whippet data processing: coordinates, diffSplicingResults, filterWhippetEvents, formatWhippetEvents, junctions, readCounts, readWhippetDIFFfiles, readWhippetDataSet, readWhippetJNCfiles, readWhippetPSIfiles

Examples

whippetFiles <- system.file("extdata","whippet/",
package = "GeneStructureTools")
wds <- readWhippetDataSet(whippetFiles)
wds <- filterWhippetEvents(wds)

gtf <- rtracklayer::import(system.file("extdata","example_gtf.gtf",
package = "GeneStructureTools"))
g <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10
whippetTranscriptChangeSummary(wds, gtf.all=gtf,BSgenome = g)