Differential expression-the next generation and beyond

RNA-sequencing (RNA-seq) technologies have not only pushed the boundaries of science, but also pushed the computational and analytic capacities of many laboratories. With respect to mapping and quantifying transcriptomes, RNA-seq has certainly established itself as the approach of choice. However, a...

Full description

Saved in:
Bibliographic Details
Published in:Briefings in functional genomics 2012-01, Vol.11 (1), p.57-62
Main Authors: Auer, Paul L., Srivastava, Sanvesh, Doerge, R.W.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Gene Expression Profiling
Multifactor Dimensionality Reduction
Research Design
Statistics as Topic
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:RNA-sequencing (RNA-seq) technologies have not only pushed the boundaries of science, but also pushed the computational and analytic capacities of many laboratories. With respect to mapping and quantifying transcriptomes, RNA-seq has certainly established itself as the approach of choice. However, as the complexities of experiments continue to grow, there is still no standard practice that allows for design, processing, normalization, efficient dimension reduction and/or statistical analysis. With this in mind, we provide a brief review of some of the key challenges that are general to all RNA-seq experiments, namely experimental design, statistical analysis and dimensionality reduction.
ISSN:2041-2649
2041-2647
2041-2657
DOI:10.1093/bfgp/elr041