Hierarchical clustering on an spectral counts matrix.

Description

Hierarchical clustering of samples in an spectral counts matrix, coloring tree branches according to factor levels.

Usage

counts.hc(msnset, do.plot=TRUE, facs=NULL, wait=TRUE)

Arguments

Details

The hierarchical clustering is done by means of hclust with default parameters. If do.plot is TRUE, a dendrogram is plotted for each factor, with branches colored as per factor level. If facs is NULL then the factors are taken from pData(msnset).

Value

Invisibly returns the the value obtained from hclust.

Author(s)

Josep Gregori

See Also

MSnSet, hclust

Examples

data(msms.dataset)
msnset <- pp.msms.data(msms.dataset)
hc <- counts.hc(msnset)
str(hc)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(msmsEDA)
Loading required package: MSnbase
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")'.

Loading required package: mzR
Loading required package: Rcpp
Loading required package: BiocParallel
Loading required package: ProtGenerics

This is MSnbase version 1.20.7 
  Read '?MSnbase' and references therein for information
  about the package and how to get started.


Attaching package: 'MSnbase'

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

    smooth

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

    trimws

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/msmsEDA/counts.hc.Rd_%03d_medium.png", width=480, height=480)
> ### Name: counts.hc
> ### Title: Hierarchical clustering on an spectral counts matrix.
> ### Aliases: counts.hc
> ### Keywords: hplot multivariate
> 
> ### ** Examples
> 
> data(msms.dataset)
> msnset <- pp.msms.data(msms.dataset)
> hc <- counts.hc(msnset)
> str(hc)
List of 7
 $ merge      : int [1:13, 1:2] -5 -7 -13 -1 -3 -10 1 4 -12 -9 ...
 $ height     : num [1:13] 48.4 57 61.8 65.7 70.5 ...
 $ order      : int [1:14] 5 6 7 8 1 2 3 4 12 13 ...
 $ labels     : chr [1:14] "U2.2502.1" "U2.2502.2" "U2.2502.3" "U2.2502.4" ...
 $ method     : chr "complete"
 $ call       : language hclust(d = dist(t(msms.counts)))
 $ dist.method: chr "euclidean"
 - attr(*, "class")= chr "hclust"
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>