Methods grown in the lab

Methods grown in the lab. Software and statistical methods developed here, grouped by what they are for. Most come with an implementation; see the linked page for code and documentation.

Network reconstruction

Algorithms to reconstruct regulatory networks from observed omics data, optionally using a reference network (for example, from pathway databases) as a starting point.

Time-lagged ordered lasso for network inference.
Post-PLSR — network inference using time-series data.

Network analysis

Methods to analyze high-throughput data in the context of pathway networks, either derived from pathway databases or inferred by other means.

GeneSurrounder — network-based identification of disease genes in expression data.
Pathway-PDM — nonlinear multi-gene analysis of gene expression data.
PoDA — pathways of distinction analysis.
Evaluating network methods — benchmarks for the above.

Circadian transcriptomics

Software to enable the optimal design and analysis of circadian gene expression experiments.

TimeCycle — a topology-inspired method for detecting cycling genes.
TimeTrial — a tool for optimizing circadian transcriptomics experiments.
TimeSignature — inferring circadian phase from gene expression.