newCountDataSet: Create a CountDataSet object

In DESeq: Differential gene expression analysis based on the negative binomial distribution

Description

This function creates a CountDataSet object from a matrix or data frame of count data.

Usage

newCountDataSet(countData, conditions, sizeFactors = NULL, phenoData = NULL, featureData = NULL)

Arguments

countData	A matrix or data frame of count data, i.e., of non-negative integer values. The rows correspond to observations (e.g., number of reads that were assigned to a gene), the columns correspond to samples (or experiments). Note that biological replicates should each get their own column, while the counts of technical replicates (i.e., several sequencing ruins/lanes from the same sample) have to be summed up into a single column.
conditions	A factor of experimental conditions (or treatments, or tissue types, or phenotypes, or the like). The length of the factor has to be equal to the number of columns of the countData matrix, assigning a condition to each sample. If 'conditions' is not a factor, it will be converted to one. Alternatively, you may pass a data frame, that will be placed in pData(cds) as is and can then be used with the modes "pooled" and "blind" in estimateVarianceFunctions and its columns can be refered top in a model formula provided to fitNbinomGLMs.
sizeFactors	This argument is deprecated. Do not use it. (Size factors should always be estimated from the data with estimateSizeFactors. If you need to set size factors manually for some reasons, change the pData(cds)$sizeFactor.
phenoData	You may pass an AnnotatedDataFrame here to describe the columns of the count matrix. Note that the package always adds two rows (or creates a new AnnotatedDataFrame with only these two rows in case you do not supply one) with names "condition" and "sizeFactor" to store this information.
featureData	You may pass an AnnotatedDataFrame here to describe the rows of the count matrix. The package will just pass through this information without using it. Note that further columns will be added to feature data later, when estimating dispersions.

Details

See also CountDataSet-class and the documentation of eSet (package Biobase) for the meaning of the other slots, which CountDataSet inherits from eSet (but which the present package does not use).

Value

an object of class CountDataSet

Author(s)

Simon Anders, [e-mail]

Examples

countsTable <- counts( makeExampleCountDataSet() )
cds <- newCountDataSet( countsTable, c( "A", "A", "A", "B", "B" ) )

Example output

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, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, 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,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

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: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: lattice
    Welcome to 'DESeq'. For improved performance, usability and
    functionality, please consider migrating to 'DESeq2'.

DESeq documentation built on April 28, 2020, 6:37 p.m.