Characterizing unknown viruses is essential for understanding viral ecology and preparing against viral outbreaks. Recovering complete genome sequences from environmental samples remains computationally challenging using metagenomics, especially for low-abundance species with uneven coverage. We present an experimental method for reliably recovering complete viral genomes from complex environmental samples.
View Article and Find Full Text PDFThe Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition's Bayesian mixture model based (BMM) metagenomics pipeline.
View Article and Find Full Text PDFCharacterizing unknown viruses is essential for understanding viral ecology and preparing against viral outbreaks. Recovering complete genome sequences from environmental samples remains computationally challenging using metagenomics, especially for low-abundance species with uneven coverage. This work presents a method for reliably recovering complete viral genomes from complex environmental samples.
View Article and Find Full Text PDF