Description Usage Arguments Details Author(s) References Examples
Generate GTF files for transcript visualization in genome browsers.
1 | generateGTF(transcriptData, filters=NULL, expressionCutoff=0,scoreMethod="local", filePrefix="spliceR_transcripts", shortDescription="SpliceR Transcripts", longDescription="Transcripts generated by SpliceR", useProgressBar=T)
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transcriptData |
A |
filters |
Vector, giving the filters that should be applied - any combinations of 'geneOK', 'expressedGenes', 'sigGenes', 'isoOK', 'expressedIso', 'isoClass' and/or 'sigIso'. Works only for data from cufflinks. |
expressionCutoff |
Numeric, giving the expression threshold (often in FPKM) used for the 'expressedGenes' and 'expressedIso' filter. Default value is 0. |
scoreMethod |
Character, either of 'local" of 'global', indicating whether to score isoform expression values for GTF color coding based on expression of the isoform in relation to the sample (global) or the gene (local). |
filePrefix |
Output file name prefix, including path. |
shortDescription |
A short description for the GTF track. |
longDescription |
A long description for the GTF track. |
useProgressBar |
Boolean, indicating whether to use progressbars. For compatibility. Default = TRUE. |
generateGTF
generates GTF files, one for each sample/condition type, and writes these to disk in the current working directory.
If the data was generated using cufflinks and the "source_id" slot of the transcriptData is set to "cufflinks", a number of filters can be applied (see spliceR
for a full description of filters).
Transcripts will be colored on a grayscale according to the scoreMethod
parameter; for "local", the isoform most expressed for a given gene symbol will be darkest; for "global", the color coding will be relative to each transcripts expression across the sample.
Kristoffer Vitting-Seerup, Johannes Waage
Vitting-Seerup K, Porse BT, Sandelin A, Waage JE. (2013) spliceR: An R package for classification of alternative splicing and prediction of coding potential from RNA-seq data. PeerJ PrePrints 1:e80v1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | #Load cufflinks example data
cuffDB <- prepareCuffExample()
#Generate SpliceRList from cufflinks data
cuffDB_spliceR <- prepareCuff(cuffDB)
#Reduce dataset size for fast example runtime
cuffDB_spliceR[[1]] <- cuffDB_spliceR[[1]][1:500]
#Run spliceR
mySpliceRList <- spliceR(cuffDB_spliceR, compareTo='preTranscript', filters=c('expressedGenes','geneOK', 'isoOK', 'expressedIso', 'isoClass'))
#Export to GTF
generateGTF(mySpliceRList, filters=c("geneOK", "isoOK", "expressedGenes", "expressedIso"), scoreMethod="local")
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