waltlabtools 0.4.3

A collection of tools for biomedical research assay analysis in Python.

A collection of tools for biomedical research assay analysis in Python.

Key Features

• Analysis for assays such as digital ELISA, 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

Getting Started

Installation

You can install waltlabtools using Anaconda (recommended) or PyPI. If you’re not comfortable with the command line, begin by installing Anaconda Navigator. Then follow these instructions 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) or pip install waltlabtools (requires pip, which should come with Python).

Dependencies

• waltlabtools requires

  • numpy ≥ 1.10

  • scipy ≥ 1.3

• If installing with pip or conda, numpy and scipy will be installed automatically

• Specific modules have additional requirements:

  • waltlabtools.read_quanterix (for importing data from Quanterix instruments) requires

    • pandas ≥ 0.25

• waltlabtools also plays well with

  • JAX for accelerated numerical computing – waltlabtools will use jax.numpy instead of numpy if jax is loaded

  • JupyterLab for interactively writing code

  • pandas for data import/export and organization

  • matplotlib for plotting

  • scikit-learn for data analysis

All of these packages can all be installed using conda or pip.

Usage

import waltlabtools as wlt  # waltlabtools main functionality
import waltlabtools.read_quanterix  # if using a Quanterix instrument

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Development of waltlabtools is led by the Walt Lab for Advanced Diagnostics at Brigham and Women’s Hospital, Harvard Medical School, and the Wyss Institute for Biologically Inspired Engineering.