reorder.genes-methods: Class a simple interface to biological data (numeric) and...

Description Arguments Format Value Public fields Active bindings Methods Examples

Description

this function reorderes the BioData object based on a column in the samples table (e.g. for plotting)

Arguments

x

the BioData object

column

the samples column to reorder on

Format

R6Class object.

Value

Object of R6Class to store BioData.

Public fields

data

the numerical data as sparse Matrix

raw

the raw numerical data as sparse Matrix

raw_intronic

the raw numerical intronic data as sparse Matrix

samples

the sample annotation as data.frame

annotation

the row annotation as data.frame

usedObj

a multi purpose list to store whichever ananlyis results do not fit in the stats list

stats

all stats with one result for each data row

ranks

currently unused

logged

a logical value stating if the data has been logged

snorm

a logical value stating if the object has been sample or cell normalized

rownamescol

which column in the annotation table contains the data rownames

sampleNamesCol

which column in the samples table contains the data rownames

outpath

where to store the object

name

the name of the object (e.g. project name)

drop=c('MDS')

currently unused

version

the version string of the BioData library that created this object

dat

the numerical data as sparse Matrix

raw

the raw numerical data as sparse Matrix

raw_intronic

the raw numerical intronic data as sparse Matrix

samples

the sample annotation as data.frame

annotation

the row annotation as data.frame

ranks

currently unused

logged

a logical value stating if the data has been logged

stats

all stats with one result for each data row

snorm

a logical value stating if the object has been sample or cell normalized

snorm

a logical value stating if the object has been sample or cell normalized

rownamescol

which column in the annotation table contains the data rownames

outpath

where to store the object

name

the name of the object (e.g. project name)

usedObj

a multi purpose list that storeas everything we forgot a slot for

Active bindings

data

the numerical data as sparse Matrix

drop=c('MDS')

currently unused

Methods

Public methods


Method print()

print a summary of the object

Usage
BioData$print()

Method new()

initialize the object - depricated - use the as_BioData functions instead

Usage
BioData$new(
  dat,
  Samples,
  annotation = NULL,
  name = "BioData",
  namecol = NULL,
  namerow = "GeneID",
  outpath = ""
)
Arguments
dat

the expression sparse Matrix

Samples

a data.frame describing the column data

annotation

a data.frame describing the row data

name

the name of the project - make it phony - will be used as filename

namecol

the column in the Samples data that is the rownames of the data Matrix

namerow

the column in the annotation data that is the rownames of the data Matrix

outpath

the path the file is stored in (defaults to getwd()) reorder a mds object based on an ordering ID This function should never be called by the user!!!


Method reorder.mds()

Usage
BioData$reorder.mds(mdsName, ids, mdsClass)
Arguments
mdsName

the name of the MDS

ids

the new order

mdsClass

the MDS class name like MDS_PCA100 reorder a BioData object based on annotation information. If the ordering data is all numeric the numeric values and not the factor levels will be used!


Method reorder.genes()

this function reorderes the BioData object based on a column in the annotation table (e.g. for plotting)

Usage
BioData$reorder.genes(column)
Arguments
column

the annotation column to reorder on reorder a BioData object based on sample information. If the ordering data is all numeric the numeric values and not the factor levels will be used!


Method reorder.samples()

this function reorderes the BioData object based on a column in the samples table (e.g. for plotting)

Usage
BioData$reorder.samples(column)
Arguments
column

the samples column to reorder on


Method data()

data accessor function either reports the dat spot or the zscored if existing

Usage
BioData$data()

Method rawData()

data accessor function either reports the dat spot or the raw if existing

Usage
BioData$rawData()

Method force.numeric()

useless and depricated

Usage
BioData$force.numeric()

Method pwd()

useless

Usage
BioData$pwd()

Method forceAbsoluteUniqueSample()

likely useless and sotherwise implemented, but makes sure all entries in the vector are unique. by default adds _1, _2, ... , _n to the not unique names

Usage
BioData$forceAbsoluteUniqueSample(x, separator = "_")
Arguments
x

the vector

separator

by default '_'


Method clone()

The objects of this class are cloneable with this method.

Usage
BioData$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

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set.seed(1)
dat = data.frame( matrix(rnorm(1000),ncol=10) ) 
colnames(dat) <- paste('Sample', 1:10)
rownames(dat) <- paste( 'gene', 1:100)
samples <- data.frame(SampleID = 1:10, sname = colnames(dat) )
annotation <- data.frame( GeneID = paste( 'gene', 1:100), Start= 101:200 )
x <- BioData$new( cbind(annotation,dat), 
	Samples=samples, name="testObject",namecol='sname', outpath = "" )

stela2502/BioData documentation built on Feb. 23, 2022, 5:47 a.m.