waltlabtools
============
.. image:: https://img.shields.io/conda/vn/tylerdougan/waltlabtools?label=Anaconda
:target: https://anaconda.org/tylerdougan/waltlabtools
:alt: Conda
.. image:: https://img.shields.io/pypi/v/waltlabtools?label=PyPI
:target: https://pypi.org/project/waltlabtools
:alt: PyPI
.. image:: https://img.shields.io/readthedocs/waltlabtools?label=Documentation
:target: https://waltlabtools.readthedocs.io/en/latest/
:alt: Documentation
.. image:: https://img.shields.io/github/repo-size/tylerdougan/waltlabtools?label=GitHub
:target: https://github.com/tylerdougan/waltlabtools
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A collection of tools for biomedical research assay analysis in Python.
Key Features
------------
- Analysis for assays such as
`digital ELISA <http://www.ncbi.nlm.nih.gov/pmc/articles/pmc2919230/>`__,
including single-molecule array (Simoa) assays
- Read instrument-generated files and calculate calibration curves,
concentrations, limits of detection, and more
- Free and open-source software under the
`GNU General Public License v3 <https://www.gnu.org/licenses/gpl-3.0.en.html>`__
Getting Started
---------------
Installation
^^^^^^^^^^^^
You can install waltlabtools using
`Anaconda <https://anaconda.org/tylerdougan/waltlabtools>`__ (recommended) or
`PyPI <https://pypi.org/project/waltlabtools/>`__. If you're not comfortable
with the command line, begin by installing
`Anaconda Navigator <https://www.anaconda.com/products/individual>`__. Then follow
`these instructions <https://docs.anaconda.com/anaconda/navigator/tutorials/manage-channels/>`__
to add the channel ``tylerdougan``, and install waltlabtools from this channel.
Alternatively, install waltlabtools from the command line with
``conda install -c tylerdougan waltlabtools`` (recommended; requires you to
first install Anaconda or
`Miniconda <https://docs.conda.io/en/latest/miniconda.html>`__) or
``pip install waltlabtools`` (requires
`pip <https://pip.pypa.io/en/stable/getting-started/>`__, which should come
with Python).
Dependencies
^^^^^^^^^^^^
- waltlabtools requires
- `numpy <https://numpy.org/doc/stable/index.html>`__ ≥ 1.10
- `scipy <https://docs.scipy.org/doc/scipy/getting_started.html>`__ ≥ 1.3
- If installing with pip or conda, numpy and scipy will be installed
automatically
- Specific modules have additional requirements:
- `waltlabtools.read <https://waltlabtools.readthedocs.io/en/latest/waltlabtools.read.html>`__
(for importing data from Quanterix instruments) requires
- `pandas <https://pandas.pydata.org>`__ ≥ 0.25
- waltlabtools also plays well with
- `JAX <https://jax.readthedocs.io/en/latest/index.html>`__
for accelerated numerical computing – waltlabtools will use jax.numpy
instead of numpy if jax is loaded
- `JupyterLab <https://jupyterlab.readthedocs.io/en/stable/>`__
for interactively writing code
- `pandas <https://pandas.pydata.org>`__
for data import/export and organization
- `matplotlib <https://matplotlib.org>`__ for plotting
- `scikit-learn <https://scikit-learn.org/stable/>`__ for data analysis
All of these packages can all be installed using
`conda <https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html>`__
or `pip <https://pypi.org>`__.
Usage
^^^^^
.. code-block:: python
import waltlabtools as wlt # waltlabtools main functionality
import waltlabtools.read_quanterix # if using a Quanterix instrument
-----
Development of waltlabtools is led by the
`Walt Lab <https://waltlab.bwh.harvard.edu>`__ for Advanced Diagnostics
at `Brigham and Women's Hospital <https://www.brighamandwomens.org>`__,
`Harvard Medical School <https://hms.harvard.edu>`__, and the
`Wyss Institute for Biologically Inspired Engineering <https://wyss.harvard.edu>`__.
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