Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

ABSTRACT:

Background

Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated.

Primary findings

A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS da

SUBMITTER: Cordero F 

PROVIDER: S-EPMC3282730 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature