Skip to content

caporaso-lab/pretrained-feature-classifiers

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Pretrained feature classifier scripts

Before you begin

Install RESCRIPt

Quickstart

  1. Run make clean to clean up the outputs dir.
  2. Ensure the database source files are present in their respective subdirs in inputs/gg and inputs/silva. Naming matters. Consult the directory listing example, below. If the SILVA data files are not present, run make getsilva to retrieve and format the SILVA reference data with RESCRIPt. If the GG files are not present, run make getgg to retrieve and import the gg_13_8 data.
  3. Ensure the FeatureData[Sequence] Artifact from the Moving Pictures tutorial is present in inputs/validation-tests, to be used for comparing FeatureData[Taxonomy] produced by the new classifiers. Consult the directory listing example, below.
  4. Copy the taxonomies produced during the last classifier-training session from <prior-session>/outputs/validation-tests to inputs/validation-tests. Note: filenames will need to be changed in the process. Consult the directory listing example, below.
  5. Run make all. GG classifiers should be done in <24hr; Silva ~24hrs.

Proposed directory listing

.
├── LICENSE
├── Makefile
├── README.md
├── inputs
│   ├── gg
│   │   ├── gg-13-8-99-seqs.qza
│   │   └── gg-13-8-99-tax.qza
│   ├── silva
│   │   ├── silva-138-99-seqs.qza
│   │   └── silva-138-99-tax.qza
│   └── validation-tests
│       ├── gg-13-8-99-expected-515-806-taxonomy.qza
│       ├── gg-13-8-99-expected-taxonomy.qza
│       ├── mp-rep-seqs.qza
│       ├── silva-138-99-expected-515-806-taxonomy.qza
│       └── silva-138-99-expected-taxonomy.qza
├── outputs
│   ├── intermediate
│   ├── logs
│   ├── pretrained-classifiers
│   └── validation-tests
└── train.sh

Env

export SKL_VERSION='0.23.1'
export Q2_VERSION='2020.2'

# prep a throwaway env, for extracting explicit package paths
conda create -n throwaway conda-forge::python==3.6 conda-forge::scikit-learn==$SKL_VERSION
conda list -n throwaway --explicit | grep 'EXPLICIT\|scikit-learn' > packages.txt

# install base env
wget https://data.qiime2.org/distro/core/qiime2-$Q2_VERSION-py36-linux-conda.yml
conda env create -n qiime2-$Q2_VERSION-skl-$SKL_VERSION --file qiime2-$Q2_VERSION-py36-linux-conda.yml

# installed override packages
conda install -n qiime2-$Q2_VERSION-skl-$SKL_VERSION --file packages.txt

# install rescript
# TODO: update to show conda install instructions
conda activate qiime2-$Q2_VERSION-skl-$SKL_VERSION
pip install git+https://github.com/bokulich-lab/RESCRIPt.git

# clean up
conda env remove -n throwaway
rm packages.txt qiime2-$Q2_VERSION-py36-linux-conda.yml

About

No description, website, or topics provided.

Resources

License

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •