metapredict performs meta-analysis of genome-wide gene expression using the elastic net. Even if you don’t plan to run the elastic net on your data, metapredict makes it straightforward to normalize your microarray data and to map probes from various platforms to Entrez Gene IDs.
LimoRhyde: a flexible approach for differential analysis of rhythmic transcriptome data, Singer and Hughey, J Biol Rhythms 2018
Evidence for widespread dysregulation of circadian clock progression in human cancer, Shilts et al., PeerJ 2018
Machine learning identifies a compact gene set for monitoring the circadian clock in human blood, Hughey, Genome Med 2017
Differential phasing between circadian clocks in the brain and peripheral organs in humans, Hughey and Butte, J Biol Rhythms 2016
ZeitZeiger: supervised learning for high-dimensional data from an oscillatory system, Hughey et al., Nucleic Acids Res 2016
Robust meta-analysis of gene expression using the elastic net, Hughey and Butte, Nucleic Acids Res 2015