دورية أكاديمية

Rigorous Statistical Methods for Rigorous Microbiome Science

التفاصيل البيبلوغرافية
العنوان: Rigorous Statistical Methods for Rigorous Microbiome Science
المؤلفون: Amy D. Willis
المصدر: mSystems, Vol 4, Iss 3 (2019)
بيانات النشر: American Society for Microbiology, 2019.
سنة النشر: 2019
المجموعة: LCC:Microbiology
مصطلحات موضوعية: hypothesis testing, machine learning, modeling, reproducibility, statistics, Microbiology, QR1-502
الوصف: ABSTRACT High-throughput sequencing has facilitated discovery in microbiome science, but distinguishing true discoveries from spurious signals can be challenging. The Statistical Diversity Lab develops rigorous statistical methods and statistical software for the analysis of microbiome and biodiversity data. Developing statistical methods that produce valid P values requires thoughtful modeling and careful validation, but careful statistical analysis reduces the risk of false discoveries and increases scientific understanding.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2379-5077
Relation: https://doaj.org/toc/2379-5077
DOI: 10.1128/mSystems.00117-19
URL الوصول: https://doaj.org/article/8a685d4d7a404b6d888906e960bb251d
رقم الأكسشن: edsdoj.8a685d4d7a404b6d888906e960bb251d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:23795077
DOI:10.1128/mSystems.00117-19