“Pitfalls in relative abundance estimation using eDNA metabarcoding”

Biomonitoring of marine vertebrates in Monterey Bay using eDNA metabarcoding

Molecular analysis of environmental DNA (eDNA) can be used to assess vertebrate biodiversity in aquatic systems, but limited work has applied eDNA technologies to marine waters. Further, there is limited understanding of the spatial distribution of vertebrate eDNA in marine waters. Here, we use an eDNA metabarcoding approach to target and amplify a hypervariable region of the mitochondrial 12S ...

Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data.

Environmental DNA (eDNA) metabarcoding is increasingly used to study the present and past biodiversity. eDNA analyses often rely on amplification of very small quantities or degraded DNA. To avoid missing detection of taxa that are actually present (false negatives), multiple extractions and amplifications of the same samples are often performed. However, the level of replication needed for rel...

Environmental DNA (eDNA) metabarcoding assays to detect invasive invertebrate species in the Great Lakes

Describing and monitoring biodiversity comprise integral parts of ecosystem management. Recent research coupling metabarcoding and environmental DNA (eDNA) demonstrate that these methods can serve as important tools for surveying biodiversity, while significantly decreasing the time, expense and resources spent on traditional survey methods. The literature emphasizes the importance of genetic m...

eDNA-based metabarcoding as a monitoring tool for fish in large lakes

Accurate Genome Relative Abundance Estimation Based on Shotgun Metagenomic Reads

Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for subsequent metagenomics analysis. Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We have developed a unified probabilistic framework (named GRAMMy) by explicitly modeling read as...