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24 results for “Software documentation”
Experimental package for "Live Software Documentation of Design Pattern Instances"
Experimental package containing the materials and data for an empirical study conducted with the DesignPatterDoc plugin for IntelliJ IDEA.
The Clarity Software Documentation Dataset
<p>This repository holds the Clarity Dataset which is a companion to the SANER'22 entitled "An Empirical Investigation into the Use of Image Captioning for Automated Software Documentation". The dataset consists of 45,998 captions 10,204 GUI screenshots and xml metadata files (akin to the "html" for stipulating GUIs) of Android applications. The NL captions were obtained from human labelers, underwent several quality control mechanisms, and contain both high- (screen-level) and low-(component) level descriptions of screen functionality. This dataset is meant as a new source of data to augment techniques for software documentation that can take advantage of the rich pixel-based information contained within screenshots.</p>
Recovering Trace Links In Software Architecture Documentation
<p>Replication Package for the dissertation "Recovering Trace Links In Software Architecture Documentation" by Jan Keim.</p> <p>The ZIP-file contains the replication package. Additionally, there is the OVA-file, which is a file to be imported as virtual machine (e.g., in VirtualBox). The virtual machine contains the replication package and everything required to run the experiments like Java, maven, dependencies etc. is installed.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (8/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (14/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (7/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (9/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (12/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (11/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (13/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (16/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Dataset for an analysis of selected studies on software development and reuse in the field of software documentation
<p>The data record contains bibliographical metadata from 2012 to 2023, which have been extracted from the databases ScienceDirect, SpringerLink and IEEE Xplore. It was created in the context of a master thesis which will be published later. The aim was to make a selection of studies on software documentation from the perspective of software development based on the master thesis.</p>
DocMine: A Software Documentation-Related Dataset of 950 GitHub Repositories
<p>DocMine dataset consists of textual information collated from multiple software artifacts, across 950 GitHub Repositories. It also consists of probable percentage contribution of text in each software artifact towards different documentation types in each repository, accompanied by metadata information about the repository such as stargazer count, number of pull requests, commits, issues and other files analyzed.</p>
Open-source Software Governance Documentation Dataset on GitHub
<p>This dataset contains 710 GitHub-hosted OSS projects, which contain a governance file in the root directory of the project. It also contains commits, issues, and comments on each project.</p>
Supplementary Material for: On the Challenges to Documenting Requirements in Agile Software Development: A Practitioners' Perspective
<p><strong>Abstract: </strong>Agile Software Development (ASD) is an iterative and incremental methodology designed to accelerate project deliveries. In this dynamic environment characterized by constant changes, the task of documenting requirements becomes increasingly challenging, leading to the emergence of the technical debt issue. This research involved a survey of 84 practitioners to identify the techniques and practices employed in documenting software requirements within ASD teams, as well as their perceptions of the documentation process and the challenges, regarding what factors influence it and its consequences. Our key findings indicate that user stories are the most commonly utilized technique by practitioners for documenting requirements. Furthermore, a deficient documentation process results in two primary consequences: rework and a knowledge deficit. To address these challenges, various techniques are implemented across different development phases, including requirement refactoring, documentation refinement meetings, and template reviews. Participants also emphasized the significance of having a requirements expert to enhance the documentation process and expressed uncertainty regarding the adequacy of their existing requirements documentation. This study highlights the growing issue of technical debt within ASD teams' documentation and requirements and raises awareness about the need to develop habits for documenting and maintaining up-to-date software requirements in agile projects.</p>
Supporting Software Maintenance with Dynamically Generated Document Hierarchies
Open the record for dataset details and reuse information.
Architecturally Significant Requirements and Software Architecture for AI-Based Systems: A Case Study with Document Classification
Open the record for dataset details and reuse information.
List of documents and patterns identified by multivocal literature review of software engineering patterns for machine learning applications
We performed a multivocal literature review of both academic and gray literature to collect software engineering for machine learning (ML) application systems and software design. For the academic literature, we chose Engineering Village. For the gray literature, we used a Google search on August 16, 2019. We retrieved 32 scholarly documents and 48 gray literature documents. We vetted whether each document should be included in our review using the following criteria: Documents written in English addressing concrete software-engineering patterns or practices to design ML application systems and software should be included. Documents focusing on design of ML techniques and algorithms should be excluded. This process identified 19 scholarly documents and 19 gray documents. Although 69 patterns related to the design of ML application systems were initially identified, 33 remained after the vetting process. Finally, industrial ML developers reviewed the 33 candidates from the viewpoint of practical usefulness. They identified only 15 ML patterns.
Emergent Solutions on Requirement Engineering for Agile Software Development: A tertiary study (Auxiliary Documentation in PDF)
<p><strong>[Context and motivation]</strong> Agile Software Development (ASD) is a new trend in software development and has become popular. Its advocates claim that ASD is well suited to solving traditional software development problems by valuing human factors over technical ones. However, one of the most critical phases in software development, Requirements Engineering (RE), can be overwhelming for ASD values.<br> <strong>[Question/problem]</strong> Trying to work with RE in a traditional way for ASD can limit ASD's potential. Therefore, it is necessary to investigate what academia and industry have done in RE to exploit all of the capabilities of ASD beyond traditional RE. <br> <strong>[Principal ideas/results]</strong> This work presents an overview of the state-of-the-art Requirement Engineering (RE) for Agile Software Development (ASD). We conducted a Tertiary Study in secondary studies published from 1st January 2015 to 30th June 2021, looking for solutions for RE-ASD using the Systematic Literature Review (SLR) protocol described by Kitchenham and Charters (2007). After executing the SLR protocol, we accepted 37 out of 169 studies and encountered 136 solutions used by academia and industry for RE-ASD. We considered only a few solutions that could be classified as emergent for RE-ASD, 24 out of 106. Furthermore, we cataloged the challenges presented by the emergent solutions (e.g., a steep learning curve due to the lack of experience, process, or culture) that should be addressed. Finally, we identified a possible gap between academia and industry regarding these emerging solutions that need further investigation. <br> <strong>[Contribution]</strong> By highlighting emerging Requirements Engineering (RE) solutions for Agile Software Development (ASD), we made our contribution to help researchers who need to propose new solutions to some of the problems that remain unsolved by pointing out the recent trends for RE for ASD.</p> <p>The repository contains the following:</p> <ul> <li>Auxiliary Documentation in PDF;</li> <li>Dataset from the Tertiary Study - compressed file (refsq2023Complement.zip): <ul> <li> <p><strong>REFSQ2023-ALL-ARTICLES.csv:</strong> is a comma-separated file with all 198 (including the duplicates) found in our search in the digital libraries with their respective status (accepted, rejected, or duplicated).</p> </li> <li> <p><strong>REFSQ2023-DISTINCT-SOLUTIONS.csv:</strong> is a comma-separated file with all the distinct solutions we found in our research. They are classified according to our classification method, explained in the article.</p> </li> <li> <p><strong>REFSQ2023-GOOGLE-TRENDS-RESULTS.csv:</strong> is a comma-separated file with all results of our query in the Google Trends tool. It also brings the used search terms and the code and classification of each solution.</p> </li> </ul> </li> </ul>
NLM Scrubber: NLM s Software Application to De-identify Clinical Text Documents
ClinicalTrials.gov study NCT02795806. IPD Sharing: NO. Countries: 1. Publications: 3.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.