MiSDEED: a synthetic data engine for microbiome study power analysis and study design.
Autor: | Chlenski P; Department of Computer Science, Columbia University, New York, NY 10027, USA., Hsu M; Department of Computer Science, Columbia University, New York, NY 10027, USA., Pe'er I; Department of Computer Science, Columbia University, New York, NY 10027, USA.; Department of Systems Biology, Columbia University, New York, NY 10027, USA.; Data Science Institute, Columbia University, New York, NY 10027, USA. |
---|---|
Jazyk: | angličtina |
Zdroj: | Bioinformatics advances [Bioinform Adv] 2022 Jun 16; Vol. 2 (1), pp. vbac043. Date of Electronic Publication: 2022 Jun 16 (Print Publication: 2022). |
DOI: | 10.1093/bioadv/vbac043 |
Abstrakt: | Summary: MiSDEED ( Mi crobial S ynthetic D ata E ngine for E xperimental D esign) is a command-line tool for generating synthetic longitudinal multinode data from simulated microbial environments. It generates relative-abundance timecourses under perturbations for an arbitrary number of time points, samples, locations and data types. All simulation parameters are exposed to the user to facilitate rapid power analysis and aid in study design. Users who want additional flexibility may also use MiSDEED as a Python package. Availability and Implementation: MiSDEED is written in Python and is freely available at https://github.com/pchlenski/misdeed. (© The Author(s) 2022. Published by Oxford University Press.) |
Databáze: | MEDLINE |
Externí odkaz: | |
Nepřihlášeným uživatelům se plný text nezobrazuje | K zobrazení výsledku je třeba se přihlásit. |