Ciona Calcium Imaging Dataset Nov 2019

Please see the attached README file for more detailsOverviewThis dataset contains calcium imaging data from various genetically defined neuronal populations in the brain of Ciona intestinalis. It also contains data from non-neuronal cells, the epidermis (CesA cells) and Trunk Lateral cells (HNK-1 cells)The data, analysis procedures, and interactive figures are all functionally linked and encapsulated in a project that can be easily explored with our free open source software platform (http://www.mesmerizelab.org/). The raw data & analysis procedures are fully transparent and traceable at the level of individual datapoints (see the "Interactive Heatmaps" example at the bottom of this page: http://www.mesmerizelab.org/Overview.html).The dataset is structured as a Mesmerize project. The easiest way to get Mesmerize is to install the snap package. Instructions are here: http://www.mesmerizelab.org/user_guides/installation.htmlOpening the datasetThe dataset is compressed as a tar archive with gzip compression. The decompressed size is 477.6 GB so make sure you have sufficient space on your filesystem. Decompression can take a while, you may get better performance if you read from a different filesystem than the one that you write to. With a 2019 i7/Ryzen 7 CPU it should take ~30 minutes if the filesystem is on an SSD. I recommend using a fast filesystem to store the decompressed data since some of the image sequences are large.pigz should be faster for decompression compared to standard tar. For Ubuntu & Debian based distros you can install pigz through apt. For other distros please check your repositories.sudo apt install pigzOn Mac OSX you can install pigz through brew. See this: https://brewinstall.org/Install-pigz-on-Mac-with-Brew/Decompressing:pigz -dc ciona_cell_types_nov11_2019_chatzigeorgiou_lab.tar.gz | tar -xfIf you cannot install pigz you can decompress with tar. This may take a long time.tar xvzf ciona_cell_types_nov11_2019_chatzigeorgiou_lab.tar.gzThe archive will unpack into a directory called "share", just navigate to "share/data/temp/kushal/" and you will see the actual dataset directory.Once decompressed, you can explore the dataset using Mesmerize. Simply open the Project Directory through the Mesmerize Welcome Window (the window that you are presented with when you launch Mesmerize). You will see the available analysis flowcharts and plots similar to this: http://www.mesmerizelab.org/Overview.html#welcome-windowSee the attached README file for more details