Last data update: 2014.03.03

 R: Class aCGH
aCGHR Documentation

Class aCGH

Description

Objects of this class represent batch of arrays of Comparative Genomic Hybridization data. In addition to that, there are slots for representing phenotype and various genomic events associated with aCGH experiments, such as transitions, amplifications, aberrations, and whole chromosomal gains and losses. Currently objects of class aCGH are represented as S3 classes which are named list of lists with functions for accessing elements of that list. In the future, it's anticipated that aCGH objects will be implemented using S4 classes and methods.

Details

One way of creating objects of class aCGH is to provide the two mandatory arguments to create.aCGH function: log2.ratios and clones.info. Alternatively aCGH object can be created using aCGH.read.Sprocs that reads Sproc data files and creates object of type aCGH.

Value

log2.ratios

Data frame containing the log2 ratios of copy number changes; rows correspond to the clones and the columns to the samples (Mandatory).

clones.info

Data frame containing information about the clones used for comparative genomic hybridization. The number of rows of clones.info has to match the number of rows in log2.ratios (Mandatory).

phenotype

Data frame containing phenotypic information about samples used in the experiment generating the data. The number of rows of phenotype has to match the number of columns in log2.ratios (Optional).

log2.ratios.imputed

Data frame containing the imputed log2 ratios. Calculate this using impute.lowess function; look at the examples below (Optional).

hmm

The structure of the hmm element is described in hmm. Calculate this using find.hmm.states function; look at the examples below (Optional).

hmm

Similar to the structure of the hmm element. Calculate this using mergeHmmStates function; look at the examples below (Optional).

sd.samples

The structure of the sd.samples element is described in computeSD.Samples. Calculate this using computeSD.Samples function; look at the examples below (Optional). It is prerequisite that the hmm states are estimated first.

genomic.events

The structure of the genomic.events element is described in find.genomic.events. Calculate this using find.genomic.events function; look also at the examples below. It is prerequisite that the hmm states and sd.samples are computed first. The genomic.events is used widely in variety of plotting functions such as plotHmmStates, plotFreqStat, and plotSummaryProfile.

dim.aCGH

returns the dimensions of the aCGH object: number of clones by number of samples.

num.clones

number of clones/number of rows of the log2.ratios data.frame.

nrow.aCGH

same as num.clones.

is.aCGH

tests if its argument is an object of class aCGH.

num.samples

number of samples/number of columns of the log2.ratios data.frame.

nrow.aCGH

same as num.samples.

num.chromosomes

number of chromosomes processed and stored in the aCGH object.

clone.names

returns the names of the clones stored in the clones.info slot of the aCGH object.

row.names.aCGH

same as clone.names.

sample.names

returns the names of the samples used to create the aCGH object. If the object is created using aCGH.read.Sprocs, these are the file names of the individual arrays.

col.names.aCGH

same as sample.names.

[.aCGH

subsetting function. Works the same way as [.data.frame.

Most of the functions/slots listed above have assignment operators '<-' associated with them.

Note

clones.info slot has to contain a list with at least 4 columns: Clone (clone name), Target (unique ID, e.g. Well ID), Chrom (chromosome number, X chromosome = 23 in human and 20 in mouse, Y chromosome = 24 in human and 21 in mouse) and kb (kb position on the chromosome).

Author(s)

Peter Dimitrov

See Also

aCGH.read.Sprocs, find.hmm.states, computeSD.Samples, find.genomic.events, plotGenome, plotHmmStates, plotFreqStat, plotSummaryProfile

Examples


## Creating aCGH object from log2.ratios and clone info files
## For alternative way look at aCGH.read.Sprocs help

datadir <- system.file(package = "aCGH")
datadir <- paste(datadir, "/examples", sep="")

clones.info <-
      read.table(file = file.path(datadir, "clones.info.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
log2.ratios <-
      read.table(file = file.path(datadir, "log2.ratios.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
pheno.type <-
      read.table(file = file.path(datadir, "pheno.type.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
ex.acgh <- create.aCGH(log2.ratios, clones.info, pheno.type)

## Printing, summary and basic plotting for objects of class aCGH

data(colorectal)
colorectal
summary(colorectal)
sample.names(colorectal)
phenotype(colorectal)
plot(colorectal)

## Subsetting aCGH object

colorectal[1:1000, 1:30]

## Imputing the log2 ratios 

log2.ratios.imputed(ex.acgh) <- impute.lowess(ex.acgh)

## Determining hmm states of the clones
## WARNING: Calculating the states takes some time

##in the interests of time, hmm-finding function is commented out
##instead the states previosuly save are assigned
##hmm(ex.acgh) <- find.hmm.states(ex.acgh)

hmm(ex.acgh) <- ex.acgh.hmm
hmm.merged(ex.acgh) <-
   mergeHmmStates(ex.acgh, model.use = 1, minDiff = .25)

## Calculating the standard deviations for each array

sd.samples(ex.acgh) <- computeSD.Samples(ex.acgh)

## Finding the genomic events associated with each sample

genomic.events(ex.acgh) <- find.genomic.events(ex.acgh)

## Plotting and printing the hmm states

plotHmmStates(ex.acgh, 1)
pdf("hmm.states.temp.pdf")
plotHmmStates(ex.acgh, 1)
dev.off()

## Plotting summary of the sample profiles

plotSummaryProfile(colorectal)

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
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(aCGH)
Loading required package: cluster
Loading required package: survival
Loading required package: multtest
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: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'aCGH'

The following object is masked from 'package:stats':

    heatmap

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/aCGH/aCGH.Rd_%03d_medium.png", width=480, height=480)
> ### Name: aCGH
> ### Title: Class aCGH
> ### Aliases: aCGH create.aCGH log2.ratios clones.info is.aCGH dim.aCGH
> ###   num.clones nrow.aCGH num.samples num.chromosomes ncol.aCGH
> ###   clone.names row.names.aCGH rownames.aCGH clone.names<-
> ###   row.names<-.aCGH rownames<-.aCGH col.names.aCGH col.names<-.aCGH
> ###   colnames.aCGH colnames<-.aCGH sample.names sample.names<-
> ###   log2.ratios.imputed log2.ratios.imputed<- hmm hmm<- hmm.merged
> ###   hmm.merged<- sd.samples sd.samples<- genomic.events genomic.events<-
> ###   phenotype phenotype<- [.aCGH print.aCGH summary.aCGH plot.aCGH minna
> ###   maxna corna floorFunc lengthNumFunc propNumFunc subset.hmm
> ###   subset.hmm.merged ex.acgh.hmm is.odd is.even
> ### Keywords: classes
> 
> ### ** Examples
> 
> 
> ## Creating aCGH object from log2.ratios and clone info files
> ## For alternative way look at aCGH.read.Sprocs help
> 
> datadir <- system.file(package = "aCGH")
> datadir <- paste(datadir, "/examples", sep="")
> 
> clones.info <-
+       read.table(file = file.path(datadir, "clones.info.ex.txt"),
+                  header = TRUE, sep = "\t", quote="", comment.char="")
> log2.ratios <-
+       read.table(file = file.path(datadir, "log2.ratios.ex.txt"),
+                  header = TRUE, sep = "\t", quote="", comment.char="")
> pheno.type <-
+       read.table(file = file.path(datadir, "pheno.type.ex.txt"),
+                  header = TRUE, sep = "\t", quote="", comment.char="")
> ex.acgh <- create.aCGH(log2.ratios, clones.info, pheno.type)
> 
> ## Printing, summary and basic plotting for objects of class aCGH
> 
> data(colorectal)
> colorectal
aCGH object
Call: aCGH.read.Sprocs(sproclist[1:40], "human.clones.info.Jul03.csv", 
    chrom.remove.threshold = 23)

Number of Arrays 40 
Number of Clones 2031 
> summary(colorectal)
aCGH object
Call: aCGH.read.Sprocs(sproclist[1:40], "human.clones.info.Jul03.csv", 
    chrom.remove.threshold = 23)

Number of Arrays 40 
Number of Clones 2031 
Imputed data exist
HMM states assigned
samples standard deviations are computed
genomic events are assigned
phenotype exists
> sample.names(colorectal)
 [1] "sprocCR31.txt"  "sprocCR40.txt"  "sprocCR43.txt"  "sprocCR59.txt" 
 [5] "sprocCR63.txt"  "sprocCR73.txt"  "sprocCR75.txt"  "sprocCR77.txt" 
 [9] "sprocCR96.txt"  "sprocCR98.txt"  "sprocCR100.txt" "sprocCR106.txt"
[13] "sprocCR112.txt" "sprocCR122.txt" "sprocCR124.txt" "sprocCR131.txt"
[17] "sprocCR135.txt" "sprocCR137.txt" "sprocCR146.txt" "sprocCR148.txt"
[21] "sprocCR150.txt" "sprocCR154.txt" "sprocCR159.txt" "sprocCR163.txt"
[25] "sprocCR169.txt" "sprocCR178.txt" "sprocCR180.txt" "sprocCR186.txt"
[29] "sprocCR193.txt" "sprocCR200.txt" "sprocCR204.txt" "sprocCR210.txt"
[33] "sprocCR212.txt" "sprocCR217.txt" "sprocCR219.txt" "sprocCR227.txt"
[37] "sprocCR232.txt" "sprocCR244.txt" "sprocCR246.txt" "sprocCR248.txt"
> phenotype(colorectal)
    id age sex stage loc           hist diff gstm1 gstt1 nqo K12 K13 MTHFR
1   31  70   0     1   0 Adenocarcinoma    1     0     1   1   1   2     2
2   40  71   0     1   1 Adenocarcinoma    1     1     1   1   2   2     2
3   43  59   1     1   0 Adenocarcinoma   NA     1     1   1   2   2     2
4   59  72   0     2   1 Adenocarcinoma    1     1     1   1   2   2     1
5   63  65   1     3   1 Adenocarcinoma    1     0     1   1   2   2     2
6   73  66   0     1   1 Adenocarcinoma    1     1     0   0   1   2     2
7   75  87   0     1   0 Adenocarcinoma    1     0     1   0   1   2     3
8   77  73   0     1   2 Adenocarcinoma    1     0     1   1   2   2     2
9   96  62   0     2   0 Adenocarcinoma    1     1     1   1   1   2     2
10  98  69   1     0   1 Adenocarcinoma    1     0     1   1   2   2     2
11 100  75   0     2   2 Adenocarcinoma    0     0     1   1   2   1     1
12 106  70   1     1   1 Adenocarcinoma    1     0     1   1   2   1     3
13 112  69   0     1   1 Adenocarcinoma    1     1     1   1   2   2     3
14 122  72   0     3   1 Adenocarcinoma    1     0     1   1   1   2     1
15 124  81   1     3   0 Adenocarcinoma    0     1     0   1   2   2     2
16 131  62   0     1   1 Adenocarcinoma    1     0     1   1   2   1     3
17 135  65   1     2   1 Adenocarcinoma    1     0     1   1   2   2     2
18 137  60   1     3   0 Adenocarcinoma    1     0     0   1   1   2     1
19 146  64   1     2   1 Adenocarcinoma    1     1     1   1   2   1     2
20 148  85   0     2   2 Adenocarcinoma    1     1     1   1   2   2     2
21 150  82   0     3   0 Adenocarcinoma    1     0     1   1   2   2     2
22 154  60   0     2   1 Adenocarcinoma    1     1     0   1   2   2     2
23 159  75   0     3   1 Adenocarcinoma    1     0     0   1   2   2     2
24 163  48   0     3   1 Adenocarcinoma    1     1     0   1   2   2     2
25 169  62   0     1   1 Adenocarcinoma    1     0     1   0   2   2     3
26 178  85   1     1   1 Adenocarcinoma    1     1     1   1   1   2     1
27 180  NA  NA    NA  NA                  NA    NA    NA  NA  NA  NA    NA
28 186  74   0     2   0 Adenocarcinoma    1     1     1   1   2   2     1
29 193  78   0     3   0 Adenocarcinoma   NA     0     1   1   2   2     2
30 200  75   1     2   1 Adenocarcinoma    1     1     0   1   2   2     2
31 204  86   1     2   0 Adenocarcinoma    0     0     0   1   2   2     1
32 210  66   1     1   2 Adenocarcinoma    1     1     0   1   1   2     2
33 212  81   1     3   0 Adenocarcinoma    0     1     1   0   2   2     1
34 217  89   0     1   0 Adenocarcinoma    1     0     1   1   2   2     1
35 219  76   1     2   0 Adenocarcinoma    1     1     1   1   2   2     3
36 227  77   0     2   1 Adenocarcinoma    1     1     1   1   2   2     3
37 232  45   1     3   2 Adenocarcinoma    1     0     1   1   2   2     2
38 244  83   0     1   1 Adenocarcinoma    1     1     1   1   2   2     2
39 246  59   1     1   2 Adenocarcinoma    1     0     1   1   2   2     1
40 248  87   0     1   0 Adenocarcinoma    1     0     1   1   1   2     1
   ERCC1 bat26 bat25 D5S346 D17S250 D2S123                             mi2
1      1     0     0      0       0      0               0/1 unstable loci
2      2     0     0      1       1      1     >2 loci unstable, (NCI def)
3      1     0     0      0       0      0               0/1 unstable loci
4     NA     0     0      0       0      0               0/1 unstable loci
5     NA     0     0      1       0      0               0/1 unstable loci
6      2     0     0      0       0      0               0/1 unstable loci
7      2     0     0      0       0      0               0/1 unstable loci
8      2     0     0      0       0      1               0/1 unstable loci
9      2     0     0      2       0      0               0/1 unstable loci
10     2     0     0      0       0      0               0/1 unstable loci
11     2     0     0      0       0      0               0/1 unstable loci
12     1     0     0      0       1      1 2 loci unstable, neither BAT-26
13     2     0     0      2       0      0               0/1 unstable loci
14     2     0     0      0       0      0               0/1 unstable loci
15     2     1     1      1       1      1                 BAT-26 unstable
16     1     0     0      0       0      0               0/1 unstable loci
17     2     0     1      2       0      0               0/1 unstable loci
18     3     0     0      0       0      0               0/1 unstable loci
19     1     0     0      0       0      2               0/1 unstable loci
20     2     0     0      0       0      0               0/1 unstable loci
21     1     0     0      0       1      1 2 loci unstable, neither BAT-26
22     2     0     0      0       0      0               0/1 unstable loci
23     1     0     0      0       0      0               0/1 unstable loci
24     1     0     0      0       0      0               0/1 unstable loci
25     1     0     0      0       0      1               0/1 unstable loci
26     3     0     0      0       0      0               0/1 unstable loci
27    NA    NA    NA     NA      NA     NA                                
28     2     0     0      0       0      0               0/1 unstable loci
29     1     0    NA     NA      NA     NA               0/1 unstable loci
30     1     0     0      0       0      0               0/1 unstable loci
31     2     1     1      1       1      1                 BAT-26 unstable
32     1     0     0      0       2      2               0/1 unstable loci
33     1     1     1      1       0      1                 BAT-26 unstable
34     1     0     0      0       2      0               0/1 unstable loci
35     1     1     1      0       0      1                 BAT-26 unstable
36     2     0     0      0       0      0               0/1 unstable loci
37     1     0     0      0       0      0               0/1 unstable loci
38     2     0     0      0       0      0               0/1 unstable loci
39     1     0     0      0       0      0               0/1 unstable loci
40     1     0     0      0       2      0               0/1 unstable loci
            LOH k12 K12AA k13 K13AA M677 M1298 p16 p14 mlh1 BAT26 mlh1c
1      negative   1   GTT   0     .    1     0   1   0    1     0     0
2      negative   0     .   0     .    1     0   0   0    0     0     0
3      negative   0     .   0     .    1     0   2   0    0     0     0
4      negative   0     .   0     .    0     1   0   1    0     0     0
5      negative   0     .   0     .    1     0   0   0    1     0     0
6      negative   1   GAT   0     .    1     1   0   0    0     0     0
7      negative   1   GAT   0     .    2     0   3   0    0     0     0
8      negative   0     .   0     .    1     1   0   0    0     0     0
9  positive LOH   1   GTT   0     .    1     0   0   0    0     0     0
10     negative   0     .   0     .    1     0   0   0    0     0     0
11     negative   0     .   1   GAC    0     2   1   0    0     0     0
12     negative   0     .   1   GAC    2     0   0   0    0     0     0
13 positive LOH   0     .   0     .    2     0   0   0    0     0     0
14     negative   1   GAT   0     .    0     2   0   0    0     0     0
15     negative   0     .   0     .    1     1   3   2    1     1     1
16     negative   0     .   1   GAC    2     0   0   0    0     0     0
17 positive LOH   0     .   0     .    1     1   1   1    0     0     0
18     negative   1   GAT   0     .    0     2   3   1    0     0     0
19 positive LOH   0     .   1   GAC    1     1   0   1    0     0     0
20     negative   0     .   0     .    1     1   0   0    0     0     0
21     negative   0     .   0     .    1     1   1   0    0     0     0
22     negative   0     .   0     .    1     0   0   0    1     0     0
23     negative   0     .   0     .    1     0   0   0    0     0     0
24     negative   0     .   0     .    1     0   0   0    0     0     0
25     negative   0     .   0     .    2     0   0   0    0     0     0
26     negative   1   GTT   0     .    0     1   0   0    0     0     0
27               NA        NA         NA    NA  NA  NA   NA    NA    NA
28     negative   0     .   0     .    0     1   0   0    1     0     0
29                0     .   0     .    1     0   1   0    0     0     0
30     negative   0     .   0     .    1     0   0   0    0     0     0
31     negative   0     .   0     .    0     2   2   1    1     1     1
32 positive LOH   1   GTT   0     .    1     1   0   0    0     0     0
33     negative   0     .   0     .    0     0   2   2    1     1     1
34 positive LOH   0     .   0     .    0     1   0   0    0     0     0
35     negative   0     .   0     .    2     0   2   2    1     1     1
36     negative   0     .   0     .    2     0   0   0    0     0     0
37     negative   0     .   0     .    1     1   0   0    0     0     0
38     negative   0     .   0     .    1     0   0   1    0     1     0
39     negative   0     .   0     .    0     1   0   0    0     0     0
40 positive LOH   1   GAT   0     .    0     1   3   0    1     0     0
                  mi misum  CGHSTAT
1  0/1 unstable loci     0 Complete
2   >2 loci unstable     3 Complete
3  0/1 unstable loci     0 Complete
4  0/1 unstable loci     0 Not Done
5  0/1 unstable loci     1 Not Done
6  0/1 unstable loci     0 Not Done
7  0/1 unstable loci     0 Complete
8  0/1 unstable loci     1 Not Done
9  0/1 unstable loci     0 Complete
10 0/1 unstable loci     0 Complete
11 0/1 unstable loci     0 Not Done
12   2 loci unstable     2 Complete
13 0/1 unstable loci     0 Complete
14 0/1 unstable loci     0 Complete
15  >2 loci unstable     5 Complete
16 0/1 unstable loci     0 Complete
17 0/1 unstable loci     1 Not Done
18 0/1 unstable loci     0 Complete
19 0/1 unstable loci     0 Not Done
20 0/1 unstable loci     0 Not Done
21   2 loci unstable     2 Not Done
22 0/1 unstable loci     0 Complete
23 0/1 unstable loci     0 Complete
24 0/1 unstable loci     0 Complete
25 0/1 unstable loci     1 Not Done
26 0/1 unstable loci     0 Not Done
27                      NA Not Done
28 0/1 unstable loci     0 Complete
29                       0 Complete
30 0/1 unstable loci     0 Not Done
31  >2 loci unstable     5 Complete
32 0/1 unstable loci     0 Complete
33  >2 loci unstable     4 Complete
34 0/1 unstable loci     0 Complete
35  >2 loci unstable     3 Not Done
36 0/1 unstable loci     0 Complete
37 0/1 unstable loci     0 Complete
38 0/1 unstable loci     0 Complete
39 0/1 unstable loci     0 Complete
40 0/1 unstable loci     0 Not Done
> plot(colorectal)
> 
> ## Subsetting aCGH object
> 
> colorectal[1:1000, 1:30]
aCGH object
Call: `[.aCGH`(colorectal, 1:1000, 1:30)

Number of Arrays 30 
Number of Clones 1000 
Warning message:
In `[.aCGH`(colorectal, 1:1000, 1:30) : subsetting the log2.ratios only
> 
> ## Imputing the log2 ratios 
> 
> log2.ratios.imputed(ex.acgh) <- impute.lowess(ex.acgh)
Processing chromosome  1 
Processing chromosome  2 
Processing chromosome  3 
Processing chromosome  4 
Processing chromosome  5 
Processing chromosome  6 
Processing chromosome  7 
Processing chromosome  8 
Processing chromosome  9 
Processing chromosome  10 
Processing chromosome  11 
Processing chromosome  12 
Processing chromosome  13 
Processing chromosome  14 
Processing chromosome  15 
Processing chromosome  16 
Processing chromosome  17 
Processing chromosome  18 
Processing chromosome  19 
Processing chromosome  20 
Processing chromosome  21 
Processing chromosome  22 
Processing chromosome  23 
> 
> ## Determining hmm states of the clones
> ## WARNING: Calculating the states takes some time
> 
> ##in the interests of time, hmm-finding function is commented out
> ##instead the states previosuly save are assigned
> ##hmm(ex.acgh) <- find.hmm.states(ex.acgh)
> 
> hmm(ex.acgh) <- ex.acgh.hmm
> hmm.merged(ex.acgh) <-
+    mergeHmmStates(ex.acgh, model.use = 1, minDiff = .25)
> 
> ## Calculating the standard deviations for each array
> 
> sd.samples(ex.acgh) <- computeSD.Samples(ex.acgh)
> 
> ## Finding the genomic events associated with each sample
> 
> genomic.events(ex.acgh) <- find.genomic.events(ex.acgh)
Finding outliers
Finding focal low level aberrations
Finding transitions
Finding focal amplifications
Processing chromosome  1 
Processing chromosome  2 
Processing chromosome  3 
Processing chromosome  4 
Processing chromosome  5 
Processing chromosome  6 
Processing chromosome  7 
Processing chromosome  8 
Processing chromosome  9 
Processing chromosome  10 
Processing chromosome  11 
Processing chromosome  12 
Processing chromosome  13 
Processing chromosome  14 
Processing chromosome  15 
Processing chromosome  16 
Processing chromosome  17 
Processing chromosome  18 
Processing chromosome  19 
Processing chromosome  20 
Processing chromosome  21 
Processing chromosome  22 
Processing chromosome  23 
Warning messages:
1: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
2: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
3: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
4: In max(indstretch[indstretch < indaber[m]]) :
  no non-missing arguments to max; returning -Inf
5: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
6: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
7: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
8: In min(indstretch[indstretch > indaber[m]]) :
  no non-missing arguments to min; returning Inf
> 
> ## Plotting and printing the hmm states
> 
> plotHmmStates(ex.acgh, 1)
> pdf("hmm.states.temp.pdf")
> plotHmmStates(ex.acgh, 1)
> dev.off()
png 
  2 
> 
> ## Plotting summary of the sample profiles
> 
> plotSummaryProfile(colorectal)
Warning messages:
1: In bxp(list(stats = c(0, 0.5, 4, 5, 10), n = 40, conf = c(2.87581029181014,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
2: In bxp(list(stats = c(0, 0, 0, 0.5, 1), n = 40, conf = c(-0.124909967576651,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
3: In bxp(list(stats = c(0, 0, 0, 0.5, 1), n = 40, conf = c(-0.124909967576651,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> 
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO