seqme: a Python library for evaluating biological sequence design

TL;DR

seqme is an open-source Python library that provides a comprehensive set of metrics for evaluating the performance of biological sequence design methods across various sequence types, enhancing reproducibility and analysis.

Contribution

It introduces a modular, extendable library with model-agnostic metrics for assessing biological sequence design, filling a gap in available software tools.

Findings

Supports diverse biological sequences including DNA, RNA, peptides, and proteins.

Includes multiple embedding and property models for evaluation.

Provides diagnostics and visualization tools for analysis.

Abstract

Recent advances in computational methods for designing biological sequences have sparked the development of metrics to evaluate these methods performance in terms of the fidelity of the designed sequences to a target distribution and their attainment of desired properties. However, a single software library implementing these metrics was lacking. In this work we introduce seqme, a modular and highly extendable open-source Python library, containing model-agnostic metrics for evaluating computational methods for biological sequence design. seqme considers three groups of metrics: sequence-based, embedding-based, and property-based, and is applicable to a wide range of biological sequences: small molecules, DNA, ncRNA, mRNA, peptides and proteins. The library offers a number of embedding and property models for biological sequences, as well as diagnostics and visualization functions to inspect the results. seqme can be used to evaluate both one-shot and iterative computational design methods.