Supported by Dr. Osamu Ogasawara and  providing  . |
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Last data update: 2014.03.03 |
Returns total number of alternative splicing eventsDescriptionReturns total number of alternative splicing events an SpliceRList. UsagetotalNumberOfAS(spliceRObject) Arguments
DetailsThis helper function returns number of total number of alternative splicing events. Object must be analyzed by ValueA vector, giving the total number of splicing events for each splice class. Author(s)Kristoffer Vitting-Seerup, Johannes Waage ReferencesVitting-Seerup K , Porse BT, Sandelin A, Waage J. (2014) spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data. BMC Bioinformatics 15:81. Examples
#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'))
#Plot number of exon skipping/inclusion events
mySpliceRList <- spliceRPlot(mySpliceRList, evaluate="nr_AS", asType="ESI")
totalNumberOfAS(mySpliceRList)
Results
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> library(spliceR)
Loading required package: cummeRbund
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Loading required package: RSQLite
Loading required package: DBI
Loading required package: ggplot2
Loading required package: reshape2
Loading required package: fastcluster
Attaching package: 'fastcluster'
The following object is masked from 'package:stats':
hclust
Loading required package: rtracklayer
Loading required package: GenomicRanges
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Gviz
Loading required package: grid
Attaching package: 'cummeRbund'
The following object is masked from 'package:GenomicRanges':
promoters
The following object is masked from 'package:IRanges':
promoters
The following object is masked from 'package:BiocGenerics':
conditions
Loading required package: VennDiagram
Loading required package: futile.logger
Loading required package: RColorBrewer
Loading required package: plyr
Attaching package: 'plyr'
The following object is masked from 'package:cummeRbund':
count
The following object is masked from 'package:IRanges':
desc
The following object is masked from 'package:S4Vectors':
rename
Attaching package: 'spliceR'
The following object is masked from 'package:cummeRbund':
conditions
The following object is masked from 'package:BiocGenerics':
conditions
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/spliceR/totalNumberOfAS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: totalNumberOfAS
> ### Title: Returns total number of alternative splicing events
> ### Aliases: totalNumberOfAS
>
> ### ** Examples
>
> #Load cufflinks example data
> cuffDB <- prepareCuffExample()
Creating database /tmp/RtmpDtGJPC/cuffData.db
Reading Run Info File /tmp/RtmpDtGJPC/run.info
Writing runInfo Table
Reading Read Group Info /tmp/RtmpDtGJPC/read_groups.info
Writing replicates Table
Reading GTF file
Writing GTF features to 'features' table...
Reading /tmp/RtmpDtGJPC/genes.fpkm_tracking
Checking samples table...
Populating samples table...
Writing genes table
Reshaping geneData table
Recasting
Writing geneData table
Reading /tmp/RtmpDtGJPC/gene_exp.diff
Writing geneExpDiffData table
Reading /tmp/RtmpDtGJPC/promoters.diff
Writing promoterDiffData table
Reading /tmp/RtmpDtGJPC/genes.count_tracking
Reshaping geneCount table
Recasting
Writing geneCount table
Reading read group info in /tmp/RtmpDtGJPC/genes.read_group_tracking
Writing geneReplicateData table
Reading /tmp/RtmpDtGJPC/isoforms.fpkm_tracking
Checking samples table...
OK!
Writing isoforms table
Reshaping isoformData table
Recasting
Writing isoformData table
Reading /tmp/RtmpDtGJPC/isoform_exp.diff
Writing isoformExpDiffData table
Reading /tmp/RtmpDtGJPC/isoforms.count_tracking
Reshaping isoformCount table
Recasting
Writing isoformCount table
Reading read group info in /tmp/RtmpDtGJPC/isoforms.read_group_tracking
Writing isoformReplicateData table
Reading /tmp/RtmpDtGJPC/tss_groups.fpkm_tracking
Checking samples table...
OK!
Writing TSS table
Reshaping TSSData table
Recasting
Writing TSSData table
Reading /tmp/RtmpDtGJPC/tss_group_exp.diff
Writing TSSExpDiffData table
Reading /tmp/RtmpDtGJPC/splicing.diff
Writing splicingDiffData table
Reading /tmp/RtmpDtGJPC/tss_groups.count_tracking
Reshaping TSSCount table
Recasting
Writing TSSCount table
Reading read group info in /tmp/RtmpDtGJPC/tss_groups.read_group_tracking
Writing TSSReplicateData table
Reading /tmp/RtmpDtGJPC/cds.fpkm_tracking
Checking samples table...
OK!
Writing CDS table
Reshaping CDSData table
Recasting
Writing CDSData table
Reading /tmp/RtmpDtGJPC/cds_exp.diff
Writing CDSExpDiffData table
Reading /tmp/RtmpDtGJPC/cds.diff
Writing CDSDiffData table
Reading /tmp/RtmpDtGJPC/cds.count_tracking
Reshaping CDSCount table
Recasting
Writing CDSCount table
Reading read group info in /tmp/RtmpDtGJPC/cds.read_group_tracking
Writing CDSReplicateData table
Indexing Tables...
Warning messages:
1: attributes are not identical across measure variables; they will be dropped
2: attributes are not identical across measure variables; they will be dropped
3: attributes are not identical across measure variables; they will be dropped
4: attributes are not identical across measure variables; they will be dropped
5: attributes are not identical across measure variables; they will be dropped
6: attributes are not identical across measure variables; they will be dropped
7: attributes are not identical across measure variables; they will be dropped
8: attributes are not identical across measure variables; they will be dropped
>
> #Generate SpliceRList from cufflinks data
> cuffDB_spliceR <- prepareCuff(cuffDB)
Reading cuffDB, isoforms...
Reading cuffDB, exons...
Analyzing cufflinks annotation problem...
Fixing cufflinks annotation problem...
Cufflinks annotation problem was fixed for 65 Cuff_genes
Creating spliceRList...
>
> #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'))
Preparing transcript data...
Converting to internal objects...
167 isoforms pre-filtering...
Filtering...
78 isoforms post-filtering...
Preparing exons...
Analyzing transcripts...
| | | 0% | |=== | 4% | |====== | 9% | |========= | 13% | |============ | 17% | |=============== | 22% | |================== | 26% | |===================== | 30% | |======================== | 35% | |=========================== | 39% | |============================== | 43% | |================================= | 48% | |===================================== | 52% | |======================================== | 57% | |=========================================== | 61% | |============================================== | 65% | |================================================= | 70% | |==================================================== | 74% | |======================================================= | 78% | |========================================================== | 83% | |============================================================= | 87% | |================================================================ | 91% | |=================================================================== | 96% | |======================================================================| 100%
Preparing output...
Done in 2.2 secs
>
> #Plot number of exon skipping/inclusion events
> mySpliceRList <- spliceRPlot(mySpliceRList, evaluate="nr_AS", asType="ESI")
Initializing (this will only happen once)...
>
> totalNumberOfAS(mySpliceRList)
ESI MEE MESI ISI A5 A3 ATSS ATTS All
32 0 5 16 10 39 33 17 152
>
>
>
>
>
> dev.off()
null device
1
>
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