Object of this class are created with the clustDist
function.
Slots
x:
Object of class list containing valid
ClustDist instances.
log:
Object of class list containing an object
creation log, containing among other elements the call that
generated the object.
.__classVersion__:
The version of the instance. For
development purposes only.
Methods
"[["
Extracts a single ClustDist at position.
"["
Extracts one of more ClustDists as
ClustDistList.
length
Returns the number of ClustDists.
names
Returns the names of ClustDists, if
available. The replacement method is also available.
show
Display the object by printing a short
summary.
lapply(x, FUN, ...)
Apply function FUN to each
element of the input x. If the application of FUN
returns and ClustDist, then the return value is an
ClustDistList, otherwise a list
.
plot
Plots a boxplot of the distance results per
protein set.
Author(s)
Lisa M Breckels <lms79@cam.ac.uk>
Examples
library('pRolocdata')
data(dunkley2006)
par <- setAnnotationParams(inputs =
c("Arabidopsis thaliana genes",
"TAIR locus ID"))
## add protein set/annotation information
xx <- addGoAnnotations(dunkley2006, par)
## filter
xx <- filterMinMarkers(xx, n = 50)
xx <- filterMaxMarkers(xx, p = .25)
## get distances for protein sets
dd <- clustDist(xx)
## plot distances for all protein sets
plot(dd)
names(dd)
## Extract first 4 ClustDist objects of the ClustDistList
dd[1:4]
## Extract 1st ClustDist object
dd[[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)
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(pRoloc)
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
Loading required package: MLInterfaces
Loading required package: annotate
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: XML
Loading required package: cluster
This is pRoloc version 1.12.4
Read '?pRoloc' and references therein for information
about the package and how to get started.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/pRoloc/ClustDistList-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ClustDistList-class
> ### Title: Storing multiple ClustDist instances
> ### Aliases: ClustDistList class:ClustDistList ClustDistList-class
> ### plot,ClustDistList,missing-method show,ClustDistList-method
> ### [,ClustDistList,ANY,ANY,ANY-method
> ### [,ClustDistList,ANY,missing,missing-method
> ### [[,ClustDistList,ANY,ANY-method [[,ClustDistList,ANY,missing-method
> ### length,ClustDistList-method names,ClustDistList-method
> ### names<-,ClustDistList,ANY-method lapply,ClustDistList-method
> ### sapply,ClustDistList-method
> ### Keywords: classes
>
> ### ** Examples
>
> library('pRolocdata')
This is pRolocdata version 1.10.0.
Use 'pRolocdata()' to list available data sets.
> data(dunkley2006)
> par <- setAnnotationParams(inputs =
+ c("Arabidopsis thaliana genes",
+ "TAIR locus ID"))
Using species Arabidopsis thaliana genes (TAIR10 (2010-09-TAIR10))
Using feature type TAIR locus ID(s)
Connecting to Biomart...
>
> ## add protein set/annotation information
> xx <- addGoAnnotations(dunkley2006, par)
Loading required namespace: GO.db
Loading required package: GO.db
>
> ## filter
> xx <- filterMinMarkers(xx, n = 50)
Retaining 16 out of 153 in GOAnnotations
> xx <- filterMaxMarkers(xx, p = .25)
Retaining 11 out of 16 in GOAnnotations
>
> ## get distances for protein sets
> dd <- clustDist(xx)
| | | 0% | |====== | 9% | |============= | 18% | |=================== | 27% | |========================= | 36% | |================================ | 45% | |====================================== | 55% | |============================================= | 64% | |=================================================== | 73% | |========================================================= | 82% | |================================================================ | 91% | |======================================================================| 100%
>
> ## plot distances for all protein sets
> plot(dd)
>
> names(dd)
[1] "mitochondrion" "vacuole"
[3] "chloroplast" "vacuolar membrane"
[5] "plasmodesma" "endoplasmic reticulum membrane"
[7] "Golgi membrane" "chloroplast envelope"
[9] "plastid" "endosome"
[11] "trans-Golgi network"
>
> ## Extract first 4 ClustDist objects of the ClustDistList
> dd[1:4]
Instance of class 'ClustDistList' containig 4 objects.
>
> ## Extract 1st ClustDist object
> dd[[1]]
Object of class "ClustDist"
fcol = GOAnnotations
term = GO:0005739
id = mitochondrion
nrow = 149
k's tested: 1 2 3 4 5
Size: 149
Size: 121
Size: 94
Size: 94
Size: 77
Clusters info:
ks.mean mean ks.norm norm
k = 1 1 0.3779 1 0.07129
k = 2 1 0.2019 1 0.04082
k = 3 1 0.1598 1 0.03515
k = 4 1 0.1598 1 0.03515
k = 5 1 *0.1289 1 *0.03029
>
>
>
>
>
> dev.off()
null device
1
>