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Challenges in benchmarking metagenomic profilers.
Sun, Zheng; Huang, Shi; Zhang, Meng; Zhu, Qiyun; Haiminen, Niina; Carrieri, Anna Paola; Vázquez-Baeza, Yoshiki; Parida, Laxmi; Kim, Ho-Cheol; Knight, Rob; Liu, Yang-Yu.
Afiliación
  • Sun Z; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Huang S; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
  • Zhang M; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA.
  • Zhu Q; Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural University, Hohhot, China.
  • Haiminen N; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
  • Carrieri AP; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA.
  • Vázquez-Baeza Y; IBM T. J. Watson Research Center, Yorktown Heights, NY, USA.
  • Parida L; IBM Research Europe, The Hartree Centre, Warrington, UK.
  • Kim HC; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
  • Knight R; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA.
  • Liu YY; IBM T. J. Watson Research Center, Yorktown Heights, NY, USA.
Nat Methods ; 18(6): 618-626, 2021 06.
Article en En | MEDLINE | ID: mdl-33986544
Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Benchmarking / Metagenómica Idioma: En Revista: Nat Methods Asunto de la revista: TECNICAS E PROCEDIMENTOS DE LABORATORIO Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Benchmarking / Metagenómica Idioma: En Revista: Nat Methods Asunto de la revista: TECNICAS E PROCEDIMENTOS DE LABORATORIO Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos