Support site for accessing data and code related to the manuscript “Subcellular pathways through VGluT3-expressing mouse amacrine cells provide locally tuned object-motion-selective signals in the retina.” (2024)
Upon publication of the manuscript, this page and its associated resources will be made public.
Viewing data and segmentations
Data relevant to the manuscript includes multiple EM and optical datasets. The most relevant dataset to the 2023 manuscript and additional data mining is the high-resolution EM dataset which is about 4 terabytes. This dataset will be made public upon publication of the 2023 manuscript. A partial dataset is available in the links below.
| Name | Links | Description | Help |
| CellNav Library (small) | Box directory Box zip file (4.7GB) | Cell surface meshes and data files that can be rendered and analyzed in CellNav. Detailed segmentations and skeletons are not included in the ‘small’ version. | Instructions |
| CellNav Library (full) | Box directory | All data that was derived from EM segmentations and subsequently used for rendering and analysis. Includes the sm###.mat files that include volume, synapse, and skeleton data for each VG3. | Instructions |
Accessing and running code
| Name | Links | Description | Help |
| CellNav | GitHub Repository Box directory Box zip file | Morgan lab Matlab app that organizes the code we use to render and analyze EM segmentations. | Instructions |
| WaferMapper | GitHub Repository | Custom matlab image acquisition software that was used to collect the EM datasets. | Publication |
| VAST | Lichtman lab download | Manual segmentation software by Daniel Berger. Published | Publication Videos |