Description Usage Arguments Details Value Author(s) Examples
Overlaps query ranges with reference ranges. The function assumes that there is no overlap between reference ranges.
1 | unifyJuncs(object)
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object |
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Many splices sites are multiple times contained when calculated from
transcripts.
In order to obtain unique splice positions the function extracts one data
set per (seqid, lend, rstart) combination.
For each site the annotation information (gene_id, strand, fexid)
is extracted from the most abundand gene name.
cnNmd
suffices: 0 <= cnNmd <= nSites. When cnNmd=0, the junction
is only present in Transcripts with biotype nonsense mediated decay
.
The returned object has the same class as the passed argument (refJunctions or derived). Therefore, it's possible to use unified junctions in the same way in downstream analysis as un-unified junctions. The contained gtf - data.frame contains the following columns:
id | Numeric index for unique site. |
seqid | Chromosome identifier |
lstart | left start |
lend | left end |
rstart | right start |
rend | right end |
nSites | Number of refJunctions (transcripts)
that contain this site. |
gene_id | Gene identifier. |
strand | Strand on which gene resides. |
fexid | Id value of first refJunction with coordinates. |
cnNmd | Number of refJunctions whose transcript_biotype is not
nonsense_mediated_decay . |
Wolfgang Kaisers
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ##-------------------------------------##
## A) Ensembl
##-------------------------------------##
ef <- system.file("extdata", "hs.ensembl.62.small.RData", package="refGenome")
ens <- loadGenome(ef)
enj <- getSpliceTable(ens)
ufe <- unifyJuncs(enj)
saveGenome(enj, "enj.RData", useBasedir=FALSE)
enjr <- loadGenome("enj.RData")
##-------------------------------------##
## B) UCSC
##-------------------------------------##
uf <- system.file("extdata", "hs.ucsc.small.RData", package="refGenome")
uc <- loadGenome(uf)
ucj <- getSpliceTable(uc)
ufu <- unifyJuncs(ucj)
saveGenome(ucj, "ucj.RData", useBasedir=FALSE)
ucjr <- loadGenome("ucj.RData")
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