دورية أكاديمية

treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

التفاصيل البيبلوغرافية
العنوان: treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses
المؤلفون: Ruizhu Huang, Charlotte Soneson, Pierre-Luc Germain, Thomas S.B. Schmidt, Christian Von Mering, Mark D. Robinson
المصدر: Genome Biology, Vol 22, Iss 1, Pp 1-21 (2021)
بيانات النشر: BMC, 2021.
سنة النشر: 2021
المجموعة: LCC:Biology (General)
LCC:Genetics
مصطلحات موضوعية: Biology (General), QH301-705.5, Genetics, QH426-470
الوصف: Abstract treeclimbR is for analyzing hierarchical trees of entities, such as phylogenies or cell types, at different resolutions. It proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single-cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1474-760X
Relation: https://doaj.org/toc/1474-760X
DOI: 10.1186/s13059-021-02368-1
URL الوصول: https://doaj.org/article/b1d8cc0b3f064bf1a238e2055b34cbd8
رقم الأكسشن: edsdoj.b1d8cc0b3f064bf1a238e2055b34cbd8
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1474760X
DOI:10.1186/s13059-021-02368-1