Tools for imperfect detection in omics data

Omics techniques are everywhere, and they are expanding how nature is studied. Omics is an umbrella term that encompasses a wide range of techniques including metagenomics, metabolomics, genomics, and transcriptomics, among others. While they study different organic molecules, omics techniques have one thing in common: they analyze pools of biological molecules, which are often unknown prior to collection, and are seldom observed in isolation. The analysis of omics data thus presents challenges which may seem unique, but are at the core of of ecological research: what needs to be standardized in sampling? How can comparability be ensured? Which technical biases affect our ability to sample communities? This session invites researchers working with omics data, statistics, and theoretical ecology to come together and discuss the limitations of omics data, and how statistical tools may help ease them.