A Python package for calculating tissue-specificity metrics for gene expression.
tspex is a tissue-specificity calculator tool. It provides both an easy-to-use object-oriented Python API and a command-line interface (CLI) for calculating a variety of tissue-specificity metrics from gene expression data.
tspex features include:
- Twelve different tissue-specificity metrics.
- Integration with popular data analysis libraries, such as NumPy, SciPy, and pandas.
- Visualization functions.
- Support for Jupyter notebooks.
A complete documentation for tspex can be found at https://apcamargo.github.io/tspex/.
There are two ways to install tspex:
- Using pip:
pip install tspex
- Using conda:
conda install -c bioconda tspex
Python API tutorial
For a detailed guide on how to use the Python API, please check the Jupyter notebook tutorial.
tspex can be executed from the command line using the
tspex command. It takes an expression matrix file as input and outputs the computed tissue-specificity values.
usage: tspex [-h] [-l] [-d] [-t THRESHOLD] input_file output_file method Compute gene tissue-specificity from an expression matrix and save the output. positional arguments: input_file Expression matrix file in the TSV, CSV or Excel formats. output_file Output TSV file containing tissue-specificity values. method Tissue-specificity metric. Allowed values are: "counts", "tau", "gini", "simpson", "shannon_specificity", "roku_specificity", "tsi", "zscore", "spm", "spm_dpm", "js_specificity", "js_specificity_dpm". optional arguments: -h, --help show this help message and exit -l, --log Log-transform expression values. (default: False) -d, --disable_transformation By default, tissue-specificity values are transformed so that they range from 0 (perfectly ubiquitous) to 1 (perfectly tissue-specific). If this parameter is used, transformation will be disabled and each metric will have have a diferent range of possible values. (default: False) -t THRESHOLD, --threshold THRESHOLD Threshold to be used with the "counts" metric. If another method is chosen, this parameter will be ignored. (default: 0)
- Using the
spmmetric to compute tissue-specificity values from a log-transformed expression matrix:
tspex --log gene_expression.tsv tspex_spm.tsv spm
- Using the
countsmethod to compute tissue-specificity by counting the number of tissues in which the gene expression is greater than 10:
tspex --threshold 10 gene_expression.tsv tspex_counts.tsv counts
- Using the
zscorewithout transformation to quantify tissue-specificity as the number of standard deviations away from the mean gene expression:
tspex --disable_transformation gene_expression.tsv tspex_zscore.tsv zscore
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