Assessing accuracy and specificity of faecal source library for microbial source-tracking, using SourceTracker as case study.

Abstract

Motivation: Understanding the quality of the source library prior to undertaking library-dependent microbial source-tracking (MST) is an essential, but often overlooked, primary analysis step.

Results: We propose an assessment approach to validate the quality of amplicon-derived faecal source libraries. This approach was demonstrated on a faecal source library consisting of 16S rRNA paired-end amplicon sequences, obtained from various animal types in Victoria, Australia. First, a leave-one-out (LOO) analysis was performed to assess the accuracy of source category groupings by identifying the number of samples incorrectly assigned to a different source category (i.e. animal type). Following a quality control procedure to decide retaining/removing/grouping incorrectly assigned samples, we then assessed if the sample sizes for each source type were sufficient to properly characterize the source fingerprints. Results from LOO demonstrated 15.5% of samples were incorrectly assigned, with high error rates in birds and wallabies within our source library. Increasing the sample size improved source identification accuracy. However, accuracy eventually plateaued in a source-specific manner. Importantly, this highlights the importance of conducting thorough assessments to understand the quality and limitations of the source library prior to library-dependent MST applications.

Availability and implementation: QIIME2 is available via https://qiime2.org/; SourceTracker v2.0.1 is available via https://github.com/caporaso-lab/sourcetracker2; Pipeline for LOO is available via https://github.com/MonashOWL/Bioinformatics-IlluminaMGI/tree/main/16S/LOO; Pipeline for sample size assessment is available via https://github.com/MonashOWL/Bioinformatics-IlluminaMGI/tree/main/16S/Source%20variability.