Supported by Dr. Osamu Ogasawara and  providing  . |
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Last data update: 2014.03.03 |
Pairs plot visualization of clusters statisticsDescriptionGraphical representation of cluster statistics, featuring pairwise correlations in the upper panel. UsageplotStatistics(clusters, corMethod = 'spearman', lower = panel.smooth, ...) Arguments
Valuecalled for its effect Author(s)Federico Comoglio See Also
Examples
require(BSgenome.Hsapiens.UCSC.hg19)
data( model, package = "wavClusteR" )
filename <- system.file( "extdata", "example.bam", package = "wavClusteR" )
example <- readSortedBam( filename = filename )
countTable <- getAllSub( example, minCov = 10, cores = 1 )
highConfSub <- getHighConfSub( countTable, supportStart = 0.2, supportEnd = 0.7, substitution = "TC" )
coverage <- coverage( example )
clusters <- getClusters( highConfSub = highConfSub,
coverage = coverage,
sortedBam = example,
method = 'mrn',
cores = 1,
threshold = 2 )
fclusters <- filterClusters( clusters = clusters,
highConfSub = highConfSub,
coverage = coverage,
model = model,
genome = Hsapiens,
refBase = 'T',
minWidth = 12 )
plotStatistics( clusters = fclusters )
Results
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> library(wavClusteR)
Loading required package: GenomicRanges
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: 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: Rsamtools
Loading required package: Biostrings
Loading required package: XVector
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/wavClusteR/plotStatistics.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotStatistics
> ### Title: Pairs plot visualization of clusters statistics
> ### Aliases: plotStatistics
> ### Keywords: graphics postprocessing
>
> ### ** Examples
>
>
> require(BSgenome.Hsapiens.UCSC.hg19)
Loading required package: BSgenome.Hsapiens.UCSC.hg19
Loading required package: BSgenome
Loading required package: rtracklayer
>
> data( model, package = "wavClusteR" )
>
> filename <- system.file( "extdata", "example.bam", package = "wavClusteR" )
> example <- readSortedBam( filename = filename )
> countTable <- getAllSub( example, minCov = 10, cores = 1 )
Loading required package: doMC
Loading required package: foreach
Loading required package: iterators
Considering substitutions, n = 497, processing in 1 chunks
chunk #: 1
considering the + strand
Computing local coverage at substitutions...
considering the - strand
Computing local coverage at substitutions...
> highConfSub <- getHighConfSub( countTable, supportStart = 0.2, supportEnd = 0.7, substitution = "TC" )
> coverage <- coverage( example )
> clusters <- getClusters( highConfSub = highConfSub,
+ coverage = coverage,
+ sortedBam = example,
+ method = 'mrn',
+ cores = 1,
+ threshold = 2 )
Computing start/end read positions
Number of chromosomes exhibiting high confidence transitions: 1
...Processing = chrX
>
> fclusters <- filterClusters( clusters = clusters,
+ highConfSub = highConfSub,
+ coverage = coverage,
+ model = model,
+ genome = Hsapiens,
+ refBase = 'T',
+ minWidth = 12 )
Computing log odds...
Refining cluster sizes...
Combining clusters...
Quantifying transitions within clusters...
Computing statistics...
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Consolidating results...
> plotStatistics( clusters = fclusters )
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> dev.off()
null device
1
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Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and