lionessR

lionessR implements the LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples) equation in R to reconstruct single-sample networks from population-level data.

Key Features:

• Single-sample network reconstruction: Extracts individual sample networks from a population using linear interpolation.
• Flexible network reconstruction methods: Runs on any network reconstruction algorithm in R that outputs a complete, weighted adjacency matrix, with Pearson correlation as the default.
• Network type compatibility: Works for both unipartite and bipartite networks.

Scientific Applications:

• Differential co-expression analysis: Identifies differential co-expression between two groups of patients, as demonstrated on a bone cancer dataset.
• Single-sample co-expression network modeling: Models co-expression networks for individual samples within a population.

Methodology:

The LIONESS equation linearly interpolates between network estimates derived from the full population and the population minus one sample to derive a single-sample network estimate.