A Python package for calculating tissue-specificity metrics for gene expression.
Project description
tspex
Overview
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 pandas.
- Visualization functions.
- Support for Jupyter notebooks.
Installation
- Using pip:
$ pip install rnasamba
- Using conda:
$ conda install -c bioconda rnasamba
Python API tutorial
For a detailed guide on how to use the Python API, please check the Jupyter notebook tutorial.
Command-line interface
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 or CSV formats.
output_file Output TSV file containing tissue-specificity values.
method Tissue-specificity metric. Allowed values are:
"counts", "tsi", "tau", "gini", "simpson",
"shannon_specificity", "roku_specificity", "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)
Examples
- Using the
spm
metric to compute tissue-specificity values from a log-transformed expression matrix:
tspex --log gene_expression.tsv tspex_spm.tsv spm
- Using the
counts
method 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
zscore
without 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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