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content/tools/analysis/deeplabcut.md

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- Versatile tracking of body parts across species
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- NWB export support through DLC2NWB
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- Integration with ndx-pose extension for standardized data storage
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## Resources
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* [Source](https://github.com/DeepLabCut/DeepLabCut)
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* [Docs](http://www.mackenziemathislab.org/deeplabcut)

content/tools/analysis/ecogvis.md

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- Create annotations
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- Mark intervals of interest
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- Built-in support for NWB files
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## Resources
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* [Source](https://github.com/catalystneuro/ecogVIS)

content/tools/analysis/movement.md

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## NWB Integration
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`movement` pose datasets can be loaded from and saved to NWB files. The pose tracks are formatted according to the [ndx-pose](https://github.com/rly/ndx-pose) extension. See the NWB tab in the [movement I/O docs](https://movement.neuroinformatics.dev/user_guide/input_output.html).
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## Resources
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* [Source](https://github.com/neuroinformatics-unit/movement)
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* [Docs](https://movement.neuroinformatics.dev/)

content/tools/analysis/neurosift.md

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```
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Replace the url query parameter with the appropriate URL for your NWB file on DANDI or anywhere else on the web.
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## Resources
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* [Source](https://github.com/flatironinstitute/neurosift)

content/tools/analysis/nwbexplorer.md

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![NWB Explorer Demo](/images/tools/nwbexplorer/nwbexplorer.gif)
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You can try NWB Explorer online at [https://nwbexplorer.v2.opensourcebrain.org](https://nwbexplorer.v2.opensourcebrain.org).
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## Resources
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* [Docs](https://nwbexplorer.v2.opensourcebrain.org)

content/tools/analysis/nwbview.md

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The release flag builds the artifacts with optimizations. Do not specify it when you need to debug.
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## Resources
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* [Source](https://github.com/brainhack-ch/nwbview)
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* [Docs](https://crates.io/crates/nwbview)

content/tools/analysis/nwbwidgets.md

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## Extending
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To extend NWBWidgets, all you need to a function that takes as input an instance of a specific neurodata_type class, and outputs a matplotlib figure or a jupyter widget.
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## Resources
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* [Source](https://github.com/NeurodataWithoutBorders/nwbwidgets)
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* [Docs](https://nwb-widgets.readthedocs.io)

content/tools/analysis/sleap.md

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- Active learning capabilities
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- Proofreading tools
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- NWB import/export support
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## Resources
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* [Source](https://github.com/talmolab/sleap)
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* [Docs](https://sleap.ai)

content/tools/core/hdmf-common-schema.md

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The HDMF Common Schema is particularly important because it defines general-purpose data structures that enable efficient and flexible representation of complex data. For example, the `DynamicTable` type provides a way to represent tabular data with columns of different data types and potentially varying numbers of rows, making it suitable for storing experimental metadata, subject information, and other tabular data.
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Understanding this schema is helpful for developers creating extensions, especially when they need to represent structured data like tables, which are common in scientific datasets.
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## Resources
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* [Source](https://github.com/hdmf-dev/hdmf-common-schema)
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* [Documentation](https://hdmf-common-schema.readthedocs.io/en/stable/)

content/tools/core/hdmf-docutils.md

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HDMF Documentation Utilities help ensure that extension documentation follows consistent formatting and includes all necessary information. This consistency improves the usability of extensions and helps users understand how to properly use them in their workflows.
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The tools can generate documentation from YAML schema files, create diagrams of data structures, and produce HTML and PDF documentation outputs.
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## Resources
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* [Source](https://github.com/hdmf-dev/hdmf-docutils)

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