DaMiR.makeSE {DaMiRseq} | R Documentation |
This is an helper function that allows the user to
simultaneously
import counts, class (mandatory) and
variables (optional) data, and creates a SummarizedExperiment
object.
DaMiR.makeSE(x, y)
x |
A tab-delimited file which contains RNA-Seq count data. Each row is a feature (i.e. gene, transcript, exon etc.) and each column is a sample |
y |
A tab-delimited file which contains experiment information. Each row is a sample and each column is a variable. This file must contain at least one column which represent 'class' information for data adjustment and classification; the class column must be labeled as 'class' |
Before creating a SummarizedExperiment
object, the
function performs some checks on input data to ensure that only a
matrix
of raw counts is accordingly loaded. Other checks allows the
identification of missing data (NA) in the data frame of the variables
of
interest.
A SummarizedExperiment
object containing raw counts,
class and (optionally) variables of interest.
Mattia Chiesa, Luca Piacentini
Morgan M, Obenchain V, Hester J and Pag\'es H (2016). SummarizedExperiment: SummarizedExperiment container. R package version 1.4.0.
rawdata.path <- system.file(package = "DaMiRseq","extdata") # import tab-delimited files: # sample data are a small subset of Genotype-Tissue Expression (GTEx) # RNA-Seq database (dbGap Study Accession: phs000424.v6.p1): count_data <- read.delim(file.path(rawdata.path, "counts_import.txt")) variables_data <- read.delim(file.path(rawdata.path, "annotation_import.txt")) # create a SummarizedExperiment object: SE <- DaMiR.makeSE(count_data, variables_data) print(SE)