Pakiet: q2-feature-table (2024.5.0+dfsg-1)

[ Pakiet źródłowy: q2-feature-table  ]

QIIME 2 plugin supporting operations on feature tables

QIIME 2 is a powerful, extensible, and decentralized microbiome analysis package with a focus on data and analysis transparency. QIIME 2 enables researchers to start an analysis with raw DNA sequence data and finish with publication-quality figures and statistical results. Key features:

 * Integrated and automatic tracking of data provenance
 * Semantic type system
 * Plugin system for extending microbiome analysis functionality
 * Support for multiple types of user interfaces (e.g. API, command line,

graphical)

QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis pipeline. QIIME 2 will address many of the limitations of QIIME 1, while retaining the features that makes QIIME 1 a powerful and widely-used analysis pipeline.

QIIME 2 currently supports an initial end-to-end microbiome analysis pipeline. New functionality will regularly become available through QIIME 2 plugins. You can view a list of plugins that are currently available on the QIIME 2 plugin availability page. The future plugins page lists plugins that are being developed.

Inne pakiety związane z q2-feature-table

• dep: python3

  Interaktywny, wysokopoziomowy i obiektowy język programowania (domyślna wersja Python 3)

• dep: python3-biom-format

  Biological Observation Matrix (BIOM) format (Python 3)

• dep: python3-h5py

  general-purpose Python interface to hdf5

• dep: python3-ipywidgets

  Interactive widgets for the Jupyter notebook (Python 3)

• dep: python3-numpy

  Szybkie zarządzanie tablicami w języku Python (Python 3)

• dep: python3-seaborn

  statistical visualization library for Python3

• dep: python3-skbio

  Python3 data structures, algorithms, educational resources for bioinformatic

• dep: q2-types (>= 2024.5)

  QIIME 2 plugin defining types for microbiome analysis

• dep: q2templates (>= 2024.5)

  Design template package for QIIME 2 Plugins

• dep: qiime (>= 2024.5)

  Quantitative Insights Into Microbial Ecology

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