mirData: Example of IsomirDataSeq with human brain miRNA counts data

Description Usage Format Author(s) Source References

Description

This data set is the object return by IsomirDataSeqFromFiles. It contains miRNA count data from 14 samples: 7 control individuals (pc) and 7 patients with Parkinson's disease in early stage (Pantano et al, 2016). Use colData to see the experiment design.

Usage

1
data("mirData")

Format

a IsomirDataSeq class.

Author(s)

Lorena Pantano, 2016-04-07

Source

Data is available from GEO dataset under accession number GSE97285

Every sample was analyzed with seqbuster tool, see http://seqcluster.readthedocs.org/mirna_annotation.html for more details. You can get same files running the small RNA-seq pipeline from https://github.com/chapmanb/bcbio-nextgen.

bcbio_nextgen was used for the full analysis.

library(isomiRs) files = list.files(file.path(root_path),pattern = "mirbase-ready", recursive = T,full.names = T) metadata_fn = list.files(file.path(root_path), pattern = "summary.csv$",recursive = T, full.names = T) metadata = read.csv(metadata_fn, row.names="sample_id") condition = names(metadata)[1] mirData <- IsomirDataSeqFromFiles(files[rownames(design)], metadata)

References

Pantano L, Friedlander MR, Escaramis G, Lizano E et al. Specific small-RNA signatures in the amygdala at premotor and motor stages of Parkinson's disease revealed by deep sequencing analysis. Bioinformatics 2016 Mar 1;32(5):673-81. PMID: 26530722


Bioconductor-mirror/isomiRs documentation built on July 28, 2017, 5:22 a.m.