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8,451 results for “Chromatin”
Accompanied data files used in the paper "Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis"
<p>lists of source file used in the paper "Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis" by Jing Yang, Amanda McGovern, Paul Martin, Kate Duffus, Xiangyu Ge, Peyman Zarrineh, Andrew P Morris, Antony Adamson, Peter Fraser, Magnus Rattray & Stephen Eyre. The paper has been accepted by Nature Communications.</p>
Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin
<p>We prepared these datasets associated with the paper “Genome-scale imaging of the 3D organization and transcriptional activity of chromatin” published in Cell: <a href="https://doi.org/10.1016/j.cell.2020.07.032">https://doi.org/10.1016/j.cell.2020.07.032</a>.</p> <p>Please find detailed descriptions of individual data files in the README_August 2020.txt.</p> <p>We provide example codes to load and analyze these datasets in: <a href="https://github.com/ZhuangLab/Chromatin_Analysis_2020_cell">https://github.com/ZhuangLab/Chromatin_Analysis_2020_cell</a>.</p> <p>If you use these datasets, please cite our Cell paper.</p>
GenomicInteractions: an R/Bioconductor package for manipulating and investigating chromatin interaction data.
<p>Files required to regenerate figures in main text of paper, using existing Supplemental R Markdown files. </p>
FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure
<p>This upload contains the FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure.</p> <p>If you use the datasets, we would be grateful if you cited the following paper:</p> <p>Zou, C., Zhang, Y., Ouyang, Z. (2016) HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology, 17: 40.</p>
Transcriptional decomposition reveals active chromatin architectures and cell specific regulatory interactions
<p><strong>Summary</strong></p> <p>Resource data across the 76 cell types from FANTOM5 analysed in our paper titled "Transcriptional decomposition reveals active chromatin architectures and cell specific regulatory interactions".</p> <p><strong>Project abstract</strong></p> <p>Gene transcription is influenced by favourable chromosome positioning and chromatin architectures bringing regulatory elements in close proximity. However, it is unclear to what extent transcription is attributable to topological organisation or to gene-specific regulatory programs. Here, we develop a strategy to transcriptionally decompose expression data into two main components reflecting the positional relationship of neighbouring transcriptional units and effects independent from their positioning. </p> <p>We demonstrate that the positionally dependent component is highly informative of topological domain activity and organisation, revealing boundaries and chromatin compartments. Furthermore, features derived from transcriptional components can accurately predict individual chromatin interactions. We systematically investigate regulatory interactions and observe different transcriptional attributes governing long- and short-range interactions. Finally, we assess differences in regulatory organisations across 76 human cell types. In all, we demonstrate a close relationship between transcription and topological chromatin architecture and provide an unprecedented resource for investigations of regulatory organisations across cell types.</p> <p><strong>Included files</strong></p> <p>PD_component_76_cell_types.tar.gz - Contains the positionally dependent (PD) components for 76 human cell types.</p> <p>PD_sd_component_76_cell_types.tar.gz - Contains the standard deviations of the positionally dependent (PD_sd) components for 76 human cell types.</p> <p>PI_component_76_cell_types.tar.gz - Contains the positionally independent (PI) components for 76 human cell types.</p> <p>PI_sd_component_76_cell_types.tar.gz - Contains the standard deviations of the positionally independent (PI_sd) components for 76 human cell types.</p> <p>predicted_EP_interactions_76_cell_types.tar.gz - Contains predicted enhancer-promoter interactions for 76 human cell types.</p> <p>predicted_boundaries_76CT.txt - Matrix with 76 columns representing human cell types and 10kb genome-wide bins as rows, coded as 0 or 1 according to whether a XAD boundary was predicted in the bin for a given cell type.</p>
SMAdd-seq: Probing chromatin accessibility with small molecule DNA intercalation and nanopore sequencing
<p>Studies of in vivo chromatin organization have relied on the accessibility of the underlying DNA to nucleases or methyltransferases, which is limited by their requirement for purified nuclei and enzymatic treatment. Here, we introduce a nanopore-based sequencing technique called Small-Molecule Adduct sequencing (SMAdd-seq), where we profile chromatin accessibility by treating nuclei or intact cells with a small molecule, angelicin. Angelicin reacts with thymine bases in linker DNA not bound to core nucleosomes after UV light exposure, thereby labeling accessible DNA regions. By applying SMAdd-seq in Saccharomyces cerevisiae, we demonstrate that angelicin-modified DNA can be detected by its distinct nanopore current signals. To systematically identify angelicin modifications and analyze chromatin structure, we developed a neural network model, NEural network for mapping MOdifications in nanopore long-reads (NEMO). NEMO accurately called expected nucleosome occupancy patterns near transcription start sites at both bulk and single-molecule levels. We observe heterogeneity in chromatin structure and identify clusters of single-molecule reads with varying configurations at specific yeast loci. Furthermore, SMAdd-seq performs equivalently on purified yeast nuclei and intact cells, indicating the promise of this method for in vivo chromatin labeling on long single molecules to measure native chromatin dynamics and heterogeneity.</p>
Oscillatory dynamics of mRNA metabolism and chromatin accessibility in mESCs during the cell cycle
<p>Processed single-cell RNAseq and multiome sequencing--single-nucleus RNAseq and ATACseq for mESCs</p> <table> <tbody> <tr> <td><strong>Filename</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>scrna_deepdycle.h5ad</td> <td>single-cell RNAseq data, has information about unsplcied and spliced levels and the inferred cell cycle phase</td> </tr> <tr> <td>snrna_deepdycle_rep1.h5ad</td> <td>single-nulceus RNAseq data (replicate 1), has information about unsplcied and spliced levels and the inferred cell cycle phase</td> </tr> <tr> <td>snrna_deepdycle_rep2.h5ad</td> <td>single-nulceus RNAseq data (replicate 2), has information about unsplcied and spliced levels and the inferred cell cycle phase</td> </tr> <tr> <td>body_coverage_lif1.tsv.gz</td> <td>single nucleus ATACseq data (replicate 1), counts table of ATACseq peaks mapped to the genes</td> </tr> <tr> <td>body_coverage_lif2.tsv.gz</td> <td>single nucleus ATACseq data (replicate 2), counts table of ATACseq peaks mapped to the genes</td> </tr> <tr> <td>model_predictions.zip</td> <td>gene-wise predictions for gene expression--unspliced and spliced, and mRNA metabolism rates--synthesis, splicing, export, and degradation rates for single-cell and single-nucleus data</td> </tr> </tbody> </table>
Predicted genome-wide chromatin contact differences among 71 bonobos and chimpanzees
<p>This file contains predicted chromatin contact differences in HFF cells using Akita among pairs of 71 bonobos and chimpanzees at 4,420 ~ 1 Mb genomic windows in the panTro6 genome. Each entry corresponds to a pairwise comparison at a given window. Data per comparison includes the individual IDs in the pairwise comparison, lineages represented, chromosome, position, window ID, mean squared error, Spearman correlation, divergence (1 - Spearman correlation), and the number of nucleotide differences for the pair at the given window.</p>
Application of flow cytometry using advanced chromatin analyses for assessing changes in the sperm structure and DNA integrity in a porcine model
<p><span>Chromatin status is critical for sperm fertility. We tested a multivariate approach for studying pig sperm chromatin, aiming to capture the chromatin structure's complexity with a set of quick and simple techniques, not only DNA damage. Sperm doses from 36 boars (3 ejaculates/boar) were analyzed at days 0 and 11 (cooled storage). Analyses were: CASA (motility) and flow cytometry to assess sperm functionality and chromatin structure by SCSA (DNA fragmentation %DFI and chromatin maturity %HDS), monobromobimane (mBBr, tiol status/disulfide bridges between protamines), chromomycin A3 (CMA3, protamination) and 8-hydroxy-2'-deoxyguanosine (8-oxo-dG, DNA oxidative damage). Data were analyzed by linear models for effects of boar and storage, correlations, and multivariate analysis as hierarchical clustering and principal component analysis (PCA). Storage reduced sperm quality parameters, mainly motility, with no critical oxidative stress increases, while chromatin status worsened slightly (%DFI and 8-oxo-dG increased while mBBr MFI and disulfide bridges decreased). Boar significantly affected most chromatin variables except for CMA3, with storage affecting most except %HDS. At day 0, sperm chromatin variables clustered closely, except for CMA3, and %HDS and 8-oxo-dG correlated with many variables (notably, mBBr). After storage, the relation between %HDS and 8-oxo-dG remained, but correlations among other techniques disappeared, and mBBr variables clustered separately. The PCA suggested a considerable influence of mBBr on sample variance, especially regarding storage, with SCSA and 8-oxo-dG affecting between-sample variability. Overall, CMA3 was the least informative, in contrast with results in other species. The combination of DNA fragmentation, DNA oxidation, chromatin compaction, and tiol status seems a good candidate for obtaining a complete picture of the pig sperm nucleus status, raising many questions for future molecular studies and deserving further research to establish its usefulness as fertility predictors in multivariate models. The meaning of CMA3 should be clarified.</span></p>
STORM Data: Transcriptionally active chromatin loops contain both 'active' and 'inactive' histone modifications that exhibit exclusivity at the level of nucleosome clusters
<p>The dataset underlying the SMLM STORM super-resolution images of 'Transcriptionally active chromatin loops contain both ‘active’ and ‘inactive’ histone modifications that exhibit exclusivity at the level of nucleosome clusters'. See Biorxiv paper for details on sample preparation: <a href="https://www.biorxiv.org/content/10.1101/2023.09.03.555774v1.full.pdf">https://www.biorxiv.org/content/10.1101/2023.09.03.555774v1.full.pdf</a>, Pyranose Oxidase STORM buffer on Elyra 7 Zeiss Microscope, processed with Zen Black. Samples are named according to which figures they occur in the above paper.</p>
Example data for chromatin interaction predictions using deepC.
<p>This archive contains example files, data and models to run deepC predictions of chromatin interactions from DNA sequence, specifically the tutorials and example commands described in the deepC repository.</p> <p>https://github.com/rschwess/deepC<br> https://github.com/rschwess/deepHaem</p> <p>Copies of the deepC and deepHaem cover are included for continuity.</p> <p>Please see the deepC publication for details:<br> Schwessinger, R., Gosden, M., Downes, D. et al. DeepC: predicting 3D genome folding using megabase-scale transfer learning. Nat Methods 17, 1118–1124 (2020). https://doi.org/10.1038/s41592-020-0960-3</p> <p>Human Hi-C is based on Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).</p> <p><br> Mouse Hi-C is based on Bonev, B. et al. Multiscale 3D genome rewiring during mouse neural development. Cell 171, 557–572.e24 (2017).</p> <p><br> DNase-seq and CTCF ChIP-seq were retrieved from the ENCODE Data portal (https://www.encodeproject.org/) Bernstein, B. E. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).</p> <p> </p>
Chromatin-IP-MS raw data
<p>Immunoprecipitated proteins by Flag-Polη were resolved by SDS-PAGE, excised and in-gel digested with trypsin, and analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) on a Thermo Orbitrap Fusion Lumos mass spectrometer.</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>
ScienceDex guides
Understand access before you commit
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.