A new tool improves the identification of diverse microbes in large datasets
In short: Researchers have developed a new software tool called Kaiju to better identify and categorize microbes in metagenomic studies. While previous methods were fast, they often struggled to identify organisms that were significantly different from those already in databases. Kaiju addresses this by focusing on protein-level matches, allowing it to classify a much larger portion of genetic data more accurately.
This matters because metagenomics is used to study everything from human health to environmental ecology, but many genetic sequences remain unclassified because they are too different from known references. Kaiju uses a specific mathematical approach called the Burrows-Wheeler transform to find matches at the protein level.
The researchers tested Kaiju against existing k-mer-based classifiers using a genome exclusion benchmark. While the study demonstrates Kaiju's high speed and sensitivity, it is a computational benchmark rather than a biological field study.
Why it matters: New software helps scientists map the hidden diversity of microbes by identifying genetic sequences that older tools missed.
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Sources
- Source: Research: Menzel et al. (2016). Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nature communications. · cc by
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