MiSDEED: a synthetic data engine for microbiome study power analysis and study design

SUMMARY: MiSDEED (Microbial Synthetic Data Engine for Experimental Design) 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, sample...

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Detalles Bibliográficos
Autores principales: Chlenski, Philippe, Hsu, Melody, Pe’er, Itsik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Application Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710642/
https://www.ncbi.nlm.nih.gov/pubmed/36699411
http://dx.doi.org/10.1093/bioadv/vbac043
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author Chlenski, Philippe
Hsu, Melody
Pe’er, Itsik
author_facet Chlenski, Philippe
Hsu, Melody
Pe’er, Itsik
author_sort Chlenski, Philippe
collection PubMed
description SUMMARY: MiSDEED (Microbial Synthetic Data Engine for Experimental Design) 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.
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spelling pubmed-97106422023-01-24 MiSDEED: a synthetic data engine for microbiome study power analysis and study design Chlenski, Philippe Hsu, Melody Pe’er, Itsik Bioinform Adv Application Note SUMMARY: MiSDEED (Microbial Synthetic Data Engine for Experimental Design) 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. Oxford University Press 2022-06-16 /pmc/articles/PMC9710642/ /pubmed/36699411 http://dx.doi.org/10.1093/bioadv/vbac043 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Application Note
Chlenski, Philippe
Hsu, Melody
Pe’er, Itsik
MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title_full MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title_fullStr MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title_full_unstemmed MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title_short MiSDEED: a synthetic data engine for microbiome study power analysis and study design
title_sort misdeed: a synthetic data engine for microbiome study power analysis and study design
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710642/
https://www.ncbi.nlm.nih.gov/pubmed/36699411
http://dx.doi.org/10.1093/bioadv/vbac043
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