epcy 0.2.6.4

Using pypi:

pip install epcy

From source:

python3 -m venv $HOME/.virtualenvs/epcy
source $HOME/.virtualenvs/epcy/bin/activate
pip install pip setuptools --upgrade
pip install wheel
cd [your_epcy_folder]
pip install -e .
epcy -h

General:

epcy -h

cd [your_epcy_folder]
python3 -m epcy -h

Generic case:

• EPCY is design to work on any quantitative data, provided that values of each feature are comparable between each samples (normalized).

• To run a comparative analysis, epcy pred need two tabulated files:

  • A matrix of quantitative normalized data for each samples (column) with an “ID” column to identify each feature.

  • A design table which describe the comparison.

# Run epcy on any normalized quantification data
epcy pred -d ./data/small_for_test/design.tsv -m ./data/small_for_test/log_normalized_matrix.tsv -o ./data/small_for_test/EPCY_output

# If your data are normalized, but require a log2 transforamtion, add --log
epcy pred --log -d ./data/small_for_test/design.tsv -m ./data/small_for_test/normalized_matrix.tsv -o ./data/small_for_test/EPCY_output

# If your data are not normalized and require a log2 transforamtion, add --norm --log
epcy pred --norm --log -d ./data/small_for_test/design.tsv -m ./data/small_for_test/matrix.tsv -o ./data/small_for_test/EPCY_output

# Different runs might show small variations.
# To ensure reproducibility set a random seed, using --randomseed
epcy pred -d ./data/small_for_test/design.tsv -m ./data/small_for_test/normalized_matrix.tsv -o ./data/small_for_test/EPCY_output --randomseed 42
epcy pred -d ./data/small_for_test/design.tsv -m ./data/small_for_test/normalized_matrix.tsv -o ./data/small_for_test/EPCY_output2 --randomseed 42
diff ./data/small_for_test/EPCY_output/predictive_capability.tsv ./data/small_for_test/EPCY_output2/predictive_capability.tsv

More documentation is available via Read the Docs.