Software

Coracle - A Machine Learning Framework to Identify Bacteria Associated with Continous Variables

Coracle is an artificial intelligence framework to identify microbes associated with a continuous physiological variable. In our case, we measured a lot of corals for their standardized coral thermal tolerance using CBASS assays with subsequent ED50 modeling (Voolstra et al. 2020; Voolstra et al 2021) and looked at prokaryote association using 16S rRNA metabarcoding. We were curious to determine whether specific prokaryotes (bacteria) were indicative of increased thermal tolerance, so we started Coracle to answer this question. But really any continuous phenotypic variable can be queried against microbial assemblage. The framework is designed to make the most out of smaller datasets and thus sacrifices efficient runtime for larger datasets. Coracle uses an ensemble approach and combines different preprocessing steps and different machine learning methods that are integrated into one comprehensible score. It is meant to be a decision-'maker' by picking prokaryote candidates for further examination.

The framework is available as a webservice at micportal.org

GitHub repository coracle

SymPortal is an analytical framework and web portal.

It is used to identify Symbiodiniaceae genotypes using Illumina rDNA ITS2 amplicon NGS data.

The web portal is available at symportal.org

GitHub repository symportal-2.0

The CBASS is a a low‐cost, portable system for standardized empirical assessments of coral acute thermal stress assays.

We provide the CBASSED50, an R package to process CBASS-derived PAM data.

Publication at Zenodo

GitHub repository CBASSED50