Journal
BIOINFORMATICS
Volume 32, Issue 12, Pages 1779-1787Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btw040
Keywords
-
Ask authors/readers for more resources
Motivation: Alignment-based taxonomic binning for metagenome characterization proceeds in two steps: reads mapping against a reference database (RDB) and taxonomic assignment according to the best hits. Beyond the sequencing technology and the completeness of the RDB, selecting the optimal configuration of the workflow, in particular the mapper parameters and the best hit selection threshold, to get the highest binning performance remains quite empirical. Results: We developed a statistical framework to perform such optimization at a minimal computational cost. Using an optimization experimental design and simulated datasets for three sequencing technologies, we built accurate prediction models for five performance indicators and then derived the parameter configuration providing the optimal performance. Whatever the mapper and the dataset, we observed that the optimal configuration yielded better performance than the default configuration and that the best hit selection threshold had a large impact on performance. Finally, on a reference dataset from the Human Microbiome Project, we confirmed that the optimized configuration increased the performance compared with the default configuration. Availability and implementation: Not applicable.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available