September 24th, 2015
Singling out microbes in the mountains of metagenomic data from complex samples, such as soil or seawater, is computationally intensive. To address this challenge, a team of researchers from the Broad Institute, led by institute member and senior author Eric Alm, and graduate student and first author Brian Cleary, created a new method – latent strain analysis (LSA) – that separates sequencing reads into biologically informed partitions and enables assembly of individual genomes, including those of bacteria that are relatively low-abundance. The team also showed that LSA is sensitive enough to separate reads from several strains of the same species. Their paper can be found in Nature Biotechnology.