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VP-CLEM-Kit: An accessible pipeline for visual proteomics using super resolution volume correlative light and electron microscopy (SR-vCLEM)

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Zenodo 13151252

License: BSD-3-Clause
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Zenodo 3773450

License: other-open
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Zenodo 15029515

License: BSD-3-Clause
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multiview-stitcher/multiview-stitcher

License: BSD-3-Clause
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napari/napari

License: BSD-3-Clause
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zarr-developers/zarr-python

License: MIT
State: the link answers
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Tools found in the code: ANTs, CuPy, h5py, imageio, Matplotlib, napari, NetworkX, Nilearn, Numba, NumPy, pandas, Pillow, scikit-image, SciPy, tifffile, xarray

Overview

Authors: Dumisile Lumkwana, Jonathan Lightley, Arturo G. Vesga, Joost de Folter, Marie-Charlotte Domart, Catherine Maclachlan, Sunil Kumar, James Evans, Christopher Peddie, Alana Burrell, Azumi Yoshimura, Asandile Mangali, Nicola Vahrjmeijer, Meenal Bhaga, Catherine Smit, Benjamin Titze, Mathew Horrocks, Lorian Cobra Straker, Edwin Garcia, Martin Jones
and 8 other authorsAdam Mclean, Candice Roufosse, Ben Loos, Sonia Gandhi, Amy Strange, Ricardo Henriques, Paul French, Lucy Collinson
Journal: bioRxiv (preprint)
Published: 10 April 2025
Type: Preprint
Status: code verified (how the code is found and verified)
DOI: 10.1101/2025.04.08.647770
License: CC BY
Institutions: The Francis Crick Institute (United Kingdom), Imperial College London (United Kingdom), Gulbenkian Institute for Molecular Medicine (Portugal), Universidade Nova de Lisboa (Portugal), Yamaguchi University (Japan), Stellenbosch University (South Africa), University of Edinburgh (United Kingdom), Imperial College Healthcare NHS Trust (United Kingdom), University College London (United Kingdom)
Categories: genetics / omics (modality), histology / microscopy (modality), human (organism), methods / tools (subfield)

Data

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