BGC detection#

In its rule-based BGC detection mode, epsSMASH first runs a set of BGC-related Hidden Markov Model (HMM) profiles on the input data and then uses manually curated rules to identify the BGCs.

The currently used rules can be found at the epsSMASH GitHub repository. In addition, the rules glossary contains a list of all current rules with extra information about their category, recent changes and links to literature for more information. Most of the epsSMASH rules (and the HMMs they use) were created using a workflow caleld epsProtocol, which you can read a short description of in HMM creation and rule building.

There are three strictness levels for the rules: strict, relaxed and loose. Strict and relaxed rules are based on the epsProtocol, while loose rules are manually curated. The default strictness is 'loose'. Read more about the hierarchy of rules in Hierarchy of rules.