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Setup for Tutorial#

Installation of napari and napari-ndev#

You have two options to download napari and napari-ndev. For users unfamiliar with using the command line and python, I would recommend following the instructions to install from UI at Beginner Setup.

If you are familiar with python, then I would recommend creating a new environment and to do a fresh installation with napari-ndev[all]. Further details available in Installation.

Download Tutorial Images and Files#

CellPainting Images#

Download Images for Example Pipeline Then, extract the files in the ZIP folder.

The images come from the Broad Bioimage Benchmark Collection. Investigate the link for the description of the images.

Scale: 0.656um/pixel

Channels:

  1. Hoescht 33342 (nuclei)
  2. con A (endoplasmic reticulum)
  3. SYTO 14 (nucleic acids: nucleoli, cytoplasmic RNA)
  4. WGA + phalloidin (plasma membrane, golgi, and actin)
  5. MitoTracker Deep Red (mitochondria)

cellpainting-image

PrimaryNeuron Images#

Download Images for Easy Machine Learning Tutorial

These images come from my own work at the University of Minnesota in the Thomas Bastian lab. The primary neurons are derived from embryonic mouse brains, and grown for a few days in a dish. The goal is to study morphology and iron homeostasis as the neurons develop over time in conditions of iron deficiency. The images available in the tutorial are extracted from multi-scene CZI files (each original file has over 100 scenes) using the Image Utilities widget. Metadata from the CZI files was correct, so the widget automatically passes this downstream without any user input.

Scale: 0.1241um/pixel

Channels:

  1. AF647 - NCOA4 / nuclear coactivator 4 (a protein known to target ferritin for degradation)
  2. AF568 - Ferritin (the iron storage protein)
  3. AF488 - Phalloidin (stains actin filaments)
  4. DAPI (nuclei)
  5. Oblique (brightfield; not always present, which is ok)

primary-neuron-image

NeuralProgenitor Images#

Download Images for Building a Pipeline Tutorial

These images come from the Zhe Chen lab at the University of Minnesota. These come from a microscope that very poorly saves the images: the images are forced to be saved as RGB (dspite having only one channel in each image) and improper scaling metadata. The images available in this tutorial have already been concatenated and the metadata applied using the Image Utilities.

Pax6 - Green; Tbr2 - Magenta

Scale: 0.7548um/pixel

Channels:

  1. PAX6 (a nuclear transcription factor identifying radial glia)
  2. PAX6-2 (a duplicate of PAX6, due to the way the microscope saves images)
  3. TBR2 (a nuclear transcription factor identifying intermediate progenitor cells)

neuralprogenitor