稀疏计数数据中的稳健aitchison复合双区
deicode的Python项目详细描述
deicode是一个工具箱,用于在稀疏的组合omics数据集上运行健壮的aitchison pca,将特定功能链接到beta多样性排序。
安装
要安装最新版本的deicode,请运行以下命令
# pip (only supported for QIIME2 >= 2018.8)
pip install deicode
# conda (only supported for QIIME2 >= 2019.1)
conda install -c conda-forge deicode
注意:deicode与python 2不兼容,并且与python 3.4或更高版本兼容。deicode当前在alpha中。我们正在积极开发它,可能会出现向后不兼容的接口更改。
将deicode用作独立工具
$ deicode --help
Usage: deicode [OPTIONS]
Runs RPCA with an rclr preprocessing step.
Options:
--in-biom TEXT Input table in biom format. [required]
--output-dir TEXT Location of output files. [required]
--n_components INTEGER The underlying low-rank structure (suggested: 1
< rank < 10) [minimum 2] [default: 3]
--min-sample-count INTEGER Minimum sum cutoff of sample across all
features [default: 500]
--min-feature-count INTEGER Minimum sum cutoff of features across all
samples [default: 10]
--max_iterations INTEGER The number of iterations to optimize the
solution (suggested to be below 100; beware of
overfitting) [minimum 1] [default: 5]
--help Show this message and exit.
在QIIME 2
其他资源
- optspace的代码从sewong oh(uiuc)维护的MATLAB package翻译成了python。
- 变换和pcoa:Scikit-bio
- 示例数据:Qiita