dmDSdata-class {DRIMSeq} | R Documentation |
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
.
## 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]
object, x |
dmDSdata object. |
... |
Other parameters that can be defined by methods using this generic. |
i, j |
Parameters used for subsetting. |
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.
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.
Malgorzata Nowicka
dmDSprecision
, dmDSfit
,
dmDStest
# -------------------------------------------------------------------------- # 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, ]