Keith Mitchell

This study evaluates ten deconvolution tools on 4,000 clinical and synthetic samples, finding EPIC performs best on Framingham data and HPCA references are generally accurate.

This study benchmarks error-correction methods for next-generation sequencing data, finding significant variation in performance across datasets with no single method being optimal overall.

The paper assesses the installability and archival stability of computational biology tools, finding many are inaccessible or hard to install, and recommends policy changes to improve these aspects.

PUMA streamlines 16S rRNA taxonomic data analysis by unifying multiple platforms and tools for efficient and reproducible microbiome research.