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BioinformaticsPLoS Computational Biology
Peer-reviewed journal article

TIPP3 and TIPP3-fast: Improved Abundance Profiling in Metagenomics

Chengze SheniD, Eleanor WedelliD, Mihai PopiD, Tandy J. WarnowiD

Abstract

We present TIPP3 and TIPP3-fast, new tools for abundance profiling in metagenomic datasets. Like its predecessor, TIPP2, the TIPP3 pipeline uses a maximum likelihood approach to place reads into labeled taxonomies using marker genes, but it achieves superior accuracy to TIPP2 by enabling the use of much larger taxonomies through improved algorithmic techniques. We show that TIPP3 outperforms leading methods for abundance profiling in two important contexts: when reads come from genomes not already in a public database (i.e., novel genomes) and when reads contain sequencing errors. We also show that TIPP3-fast has slightly lower accuracy than TIPP3, but is still more accurate than other leading methods and uses a small fraction of TIPP3s runtime. Additionally, we highlight the potential benefits of restricting abundance profiling methods to those reads that map to marker genes (i.e., using a filtered marker-gene based analysis), which we show typically improves accuracy. TIPP3 is freely available at https://github.com/c5shen/TIPP3. Author summaryTIPP3 is a new marker gene-based abundance profiling tool that builds on TIPP and TIPP2 with significant enhancements. TIPP3 supports larger reference packages ([~] 55,000 sequences per marker gene) and achieves higher accuracy in abundance profiling, especially with challenging input reads containing sequencing errors or novel genomes. TIPP3 outperforms TIPP2 and other leading methods in profiling accuracy, and its fast version TIPP3-fast is competitive in runtime with the competing methods while being more accurate under challenging conditions. TIPP3 is open-source and available at https://github.com/c5shen/TIPP3.

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