mSystems
(Aug 2021)
Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing
Matthew Y. Cho,
Marc Oliva,
Anna Spreafico,
Bo Chen,
Xu Wei,
Yoojin Choi,
Rupert Kaul,
Lillian L. Siu,
Bryan Coburn,
Pierre H. H. Schneeberger
Affiliations
Matthew Y. Cho
Department of Medicine, University of Toronto, Toronto, Canada
Marc Oliva
Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
Anna Spreafico
Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
Bo Chen
Department of Biostatistics, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
Xu Wei
Department of Biostatistics, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
Yoojin Choi
Department of Medicine, University of Toronto, Toronto, Canada
Rupert Kaul
Department of Medicine, University of Toronto, Toronto, Canada
Lillian L. Siu
Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
Bryan Coburn
ORCiD Department of Medicine, University of Toronto, Toronto, Canada
Pierre H. H. Schneeberger
ORCiD Department of Medicine, University of Toronto, Toronto, Canada
DOI
https://doi.org/10.1128/mSystems.00552-21
Journal volume & issue
Vol. 6,
no. 4
Abstract
Read online
When determining human microbiota composition, shotgun sequencing is a powerful tool that can generate large amounts of data. However, in sample compositions with low or variable microbial density, shallowing sequencing can negatively affect resulting data.
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