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, 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.
Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Paul L
PL
Auer
Sanvesh
S
Srivastava
R W
RW
Doerge
D001185:Artificial Intelligence; D020869:Gene Expression Profiling; D058011:Multifactor Dimensionality Reduction; D012107:Research Design; D013223:Statistics as Topic