The name of the main copy number. That is "CN2" for diploid
individuals. For haplocn.mops this should be set to "CN1".
sampleIdx
The index of the samples to be plotted. (Default = missing)
seqnames
The names of the reference sequence (chromosomes) to
be plotted. (Default = missing)
segStat
Whether the segment line should display the mean or the
median of a segments calls. (Default = "mean").
plot.type
the type of plot. (Default = "s").
altcol
logical flag to indicate if chromosomes should be
plotted in alternating colors in the whole genome plot. (Default = TRUE).
sbyc.layout
layout settings for the multifigure grid layout
for the ‘samplebychrom’ type. It should be specified as a vector of
two integers which are the number of rows and columns. The default
values are chosen based on the number of chromosomes to produce a
near square graph. For normal genome it is 4x6 (24 chromosomes)
plotted by rows. (Default = NULL).
cbys.nchrom
the number of chromosomes per page in the layout.
(Default = 1).
cbys.layout
layout settings for the multifigure grid layout
for the ‘chrombysample’ type. As above it should be specified as
number of rows and columns and the default chosen based on the
number of samples. (Default = NULL).
include.means
logical flag to indicate whether segment means
are to be drawn. (Default = TRUE).
zeroline
logical flag to indicate whether a horizontal line at
y=0 is to be drawn. (Default = TRUE).
pt.pch
the plotting character used for plotting the log-ratio
values. (Default = ".")
pt.cex
the size of plotting character used for the log-ratio
values (Default = 3).
pt.cols
the color list for the points. The colors alternate
between chromosomes. (Default = c("green","black").)
segcol
the color of the lines indicating the segment means.
(Default = "red").
zlcol
the color of the zeroline. (Default = "grey").
ylim
this argument is present to override the default limits
which is the range of symmetrized log-ratios. (Default = NULL).
lwd
line weight of lines for segment mean and zeroline. (Default = 3).
...
other arguments which will be passed to plot
commands.
data(cn.mops)
r <- cn.mops(X[1:200, ])
segplot(r,sampleIdx=1)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(cn.mops)
Loading required package: parallel
Loading required package: GenomicRanges
Loading required package: BiocGenerics
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
Attaching package: 'cn.mops'
The following object is masked from 'package:S4Vectors':
params
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cn.mops/segplot-CNVDetectionResult-method.Rd_%03d_medium.png", width=480, height=480)
> ### Name: segplot,CNVDetectionResult-method
> ### Title: Visualization of a CNV detection result.
> ### Aliases: segplot,CNVDetectionResult-method
>
> ### ** Examples
>
> data(cn.mops)
> r <- cn.mops(X[1:200, ])
Normalizing...
Starting local modeling, please be patient...
Reference sequence: undef
Starting segmentation algorithm...
Using "fastseg" for segmentation.
> segplot(r,sampleIdx=1)
Segplot might not work because of special characters in the sample names. Use only A-Z,a-z and 0-9!
There is a hidden function cn.mops:::.replaceNames that replaces the names in the "CNVDetectionResult" object.
>
>
>
>
>
> dev.off()
null device
1
>