PhenoFeatureFinder: a python package for linkingdevelopmental phenotypes to omics features

PhenoFeatureFinder is designed to facilitate the analyses required to analyse quantitative and/or progressive phenotypic-and omics data, and link those using Machine Learning with the aim to identify causal features, in one package.It can be used for 1) evaluation and visualisation of phenotype progression over multiple stages and between groups (e.g.treatments, genotypes), 2) pre-processing of omics data, and 3) prediction of features that explain the phenotypic classification.To facilitate usability, each step in the pipeline can also be performed independently, hence has been assigned a class in the package (Figure 1).We provide an example of implementation below that focuses on insect development through time and the selection of metabolic features causal to the observed phenotype, but different input data could be used, provided it has a similar structure.This could be any phenotype that is scored in progressive stages over time.Also, PhenoFeatureFinder was developed initially with metabolomics data, but users can evaluate its fit applying other types of omics data.