zenodoopen

Synthetic Data for Neutrophil Analysis: Sets with regular shapes and Gaussian noise

Synthetic Datasets with regular shapes and Gaussian noise. Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):   https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636 http://www.phagosight.org https://github.com/phagosight/phagosight   A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames. Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation.  Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by Gaussian distributions of higher intensities than the background and Gaussian noise (check the corresponding irregular shapes with Poisson noise plus another set with a single large neutrophil and Poisson noise). The orientation of the Gaussians varied according to the displacement of the artificial neutrophils, i.e.they were round when the cells were static, or elongated when in movement. The tracks with the Gaussians were saved as the gold standard and five different data sets were generated by adding varying levels of white Gaussian noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.   Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 6): <ul> <li>    x,y,t trajectories    ThreeDTracks</li> <li>    Ground Truth       syntheticData0_mat_Re </li> <li>    First data set         syntheticData1_mat_Re</li> <li>    Second data set     syntheticData2_mat_Re</li> <li>    Third data set       syntheticData3_mat_Re</li> <li>    Fourth data set     syntheticData4_mat_Re</li> <li>    Fifth data set         syntheticData5_mat_Re</li> <li>    Sixth data set         syntheticData6_mat_Re</li> </ul>   Corresponding GIF files are also included as illustrations of the cells in motion.   Main Reference: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636">PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model </a> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship: 8
Harmonization: 8
Access: 16
Reuse readiness: 8
Engagement: 0

Topics

Cell Tracking Cell Segmentation Neutrophils Phagocytes PhagoSight Matlab Ground Truth Synthetic Data zebrafish