Community-led, integrated, reproducible multi-omics with anvi'o

Publikation: Bidrag til tidsskriftLederForskningfagfællebedømt

  • A. Murat Eren
  • Evan Kiefl
  • Alon Shaiber
  • Iva Veseli
  • Samuel E. Miller
  • Matthew S. Schechter
  • Isaac Fink
  • Jessica N. Pan
  • Mahmoud Yousef
  • Emily C. Fogarty
  • Florian Trigodet
  • Andrea R. Watson
  • Ozcan C. Esen
  • Ryan M. Moore
  • Quentin Clayssen
  • Michael D. Lee
  • Veronika Kivenson
  • Elaina D. Graham
  • Bryan D. Merrill
  • Antti Karkman
  • Daniel Blankenberg
  • John M. Eppley
  • Andreas Sjodin
  • Jarrod J. Scott
  • Xabier Vazquez-Campos
  • Luke J. McKay
  • Elizabeth A. McDaniel
  • Sarah L. R. Stevens
  • Rika E. Anderson
  • Jessika Fuessel
  • Lois Maignien
  • Tom O. Delmont
  • Amy D. Willis

Big data abound in microbiology, but the workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked. Five years after anvi'o was first published, this community-led multi-omics platform is maturing into an open software ecosystem that reduces constraints in 'omics data analyses.

OriginalsprogEngelsk
TidsskriftNature Microbiology
Vol/bind6
Udgave nummer1
Sider (fra-til)3-6
Antal sider4
ISSN2058-5276
DOI
StatusUdgivet - 2021

ID: 256274216