SparseDataSet-class: Class '"SparseDataSet"'

In mikelove/SparseData: Efficient Manipulation of Sparse Experiment Data

Description

An extension of the eSet class for sparse matrix data. The assay data is stored as a dgCMatrix and accessible via the sparseData function.

The dgCMatrix-class is compressed, sparse, column-oriented format. This class is convenient because the typical high-throughput assay data is a tall matrix: perhaps hundreds of samples defined over thousands or millions of features. Distances and correlations between samples can be calculated quickly using matrix multiplication.

Objects from the Class

Objects can be created with calls to newSparseDataSet.

Slots

means:

Object of class "list" ~~

sumSquares:

Object of class "list" ~~

tStats:

Object of class "list" ~~

assayData:

Object of class "AssayData" ~~

phenoData:

Object of class "AnnotatedDataFrame" ~~

featureData:

Object of class "AnnotatedDataFrame" ~~

experimentData:

Object of class "MIAxE" ~~

annotation:

Object of class "character" ~~

protocolData:

Object of class "AnnotatedDataFrame" ~~

.__classVersion__:

Object of class "Versions" ~~

Extends

Class "eSet", directly. Class "VersionedBiobase", by class "eSet", distance 2. Class "Versioned", by class "eSet", distance 3.

Methods

sparseData

signature(object = "SparseDataSet"): ...

conditions

signature(object = "SparseDataSet"): ...

combine

signature(object = "SparseDataSet"), signature(object = "SparseDataSet"): ...

calculateMeans

signature(object = "SparseDataSet"): ...

means

signature(object = "SparseDataSet"): ...

means<-

signature(object = "SparseDataSet"): ...

sumSquares

signature(object = "SparseDataSet"): ...

sumSquares<-

signature(object = "SparseDataSet"): ...

calculateTStats

signature(object = "SparseDataSet"): ...

tStats

signature(object = "SparseDataSet"): ...

tStats<-

signature(object = "SparseDataSet"): ...

Author(s)

Michael Love

mikelove/SparseData documentation built on May 22, 2019, 10:52 p.m.