Detection of low-abundance bacterial strains in metagenomic datasets by eigengenome partitioning

Detection of low-abundance bacterial strains in metagenomic datasets by eigengenome partitioning

Analyses of metagenomic datasets that are sequenced to a depth of billions or trillions of bases can uncover hundreds of microbial genomes, but naive assembly of these data is computationally intensive, requiring hundreds of gigabytes to terabytes of RAM. We present latent strain analysis (LSA), a s...

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Bibliographic Details
Main Authors: Huang, Katherine, Gevers, Dirk, Shea, Terrance, Young, Sarah, Cleary, Brian Lowman, Brito, Ilana Lauren, Alm, Eric J
Other Authors: Massachusetts Institute of Technology. Computational and Systems Biology Program
Format: Article
Language:en_US
Published: Nature Publishing Group 2017
Online Access:http://hdl.handle.net/1721.1/106576
https://orcid.org/0000-0003-0825-7129
https://orcid.org/0000-0001-8294-9364

Internet

http://hdl.handle.net/1721.1/106576
https://orcid.org/0000-0003-0825-7129
https://orcid.org/0000-0001-8294-9364

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