DaMiR.makeSE: Import RNA-Seq count data and variables

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/helper.R

Description

This is an helper function that allows the user to simultaneously import counts, class (mandatory) and variables (optional) data, and creates a SummarizedExperiment object.

Usage

1

Arguments

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'

Details

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.

Value

A SummarizedExperiment object containing raw counts, class and (optionally) variables of interest.

Author(s)

Mattia Chiesa, Luca Piacentini

References

Morgan M, Obenchain V, Hester J and Pag\'es H (2016). SummarizedExperiment: SummarizedExperiment container. R package version 1.4.0.

See Also

SummarizedExperiment

Examples

1
2
3
4
5
6
7
8
9
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)

DaMiRseq documentation built on Dec. 2, 2018, 6:01 p.m.