EvalDNA: a machine learning-based tool for the comprehensive evaluation of mammalian genome assembly quality.

ABSTRACT:

Background

To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment.

Results

EvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence bas

SUBMITTER: MacDonald ML 

PROVIDER: S-EPMC8627028 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature