dmDSdata-class: dmDSdata object

In markrobinsonuzh/DRIMSeq: Differential transcript usage and tuQTL analyses with Dirichlet-multinomial model in RNA-seq

Description

dmDSdata contains expression, in counts, of genomic features such as exons or transcripts and sample information needed for the differential exon/transcript usage (DEU or DTU) analysis. It can be created with function dmDSdata.

Usage

## S4 method for signature 'dmDSdata'
counts(object)

samples(x, ...)

## S4 method for signature 'dmDSdata'
samples(x)

## S4 method for signature 'dmDSdata'
names(x)

## S4 method for signature 'dmDSdata'
length(x)

## S4 method for signature 'dmDSdata,ANY'
x[i, j]

Arguments

object, x	dmDSdata object.
...	Other parameters that can be defined by methods using this generic.
i, j	Parameters used for subsetting.

Value

• counts(object): Get a data frame with counts.

• samples(x): Get a data frame with the sample information.

• names(x): Get the gene names.

• length(x): Get the number of genes.

• x[i, j]: Get a subset of dmDSdata object that consists of counts for genes i and samples j.

Slots

counts

MatrixList of expression, in counts, of genomic features. Rows correspond to genomic features, such as exons or transcripts. Columns correspond to samples. MatrixList is partitioned in a way that each of the matrices in a list contains counts for a single gene.

samples

Data frame with information about samples. It must contain sample_id variable with unique sample names and other covariates that desribe samples and are needed for the differential analysis.

Author(s)

Malgorzata Nowicka

See Also

dmDSprecision, dmDSfit, dmDStest

Examples

# --------------------------------------------------------------------------
# Create dmDSdata object 
# --------------------------------------------------------------------------
## Get kallisto transcript counts from the 'PasillaTranscriptExpr' package

library(PasillaTranscriptExpr)

data_dir  <- system.file("extdata", package = "PasillaTranscriptExpr")

## Load metadata
pasilla_metadata <- read.table(file.path(data_dir, "metadata.txt"), 
header = TRUE, as.is = TRUE)

## Load counts
pasilla_counts <- read.table(file.path(data_dir, "counts.txt"), 
header = TRUE, as.is = TRUE)

## Create a pasilla_samples data frame
pasilla_samples <- data.frame(sample_id = pasilla_metadata$SampleName, 
  group = pasilla_metadata$condition)
levels(pasilla_samples$group)

## Create a dmDSdata object
d <- dmDSdata(counts = pasilla_counts, samples = pasilla_samples)

## Use a subset of genes, which is defined in the following file
gene_id_subset <- readLines(file.path(data_dir, "gene_id_subset.txt"))

d <- d[names(d) %in% gene_id_subset, ]

markrobinsonuzh/DRIMSeq documentation built on May 21, 2019, 12:23 p.m.