Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (7/16)

Name: Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (7/16)
Creator: Zenodo
Published: 2022-05-01T21:55:15+08:00

Zenodo2022-07-29 更新2026-05-25 收录

数据链接：

https://zenodo.org/record/6510099 数据链接链接失效反馈

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资源简介：

Data, software and documentation to reproduce the results presented in [Keizer et al. (2022) ‘Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics’ Science, 377:6605, DOI: 10.1126/science.abi9810]. Description Location Centralized GitHub repository with: Local copy of all the code and trajectory/force files Jupyter notebooks to make all the graphs in Keizer et al. Pointers to all the datasets also shown in this table Keizer et al. repository Raw microscopy data: Experiments performed with the 30’-PR scheme Experiment performed with the 100”-PR scheme Experiment performed with high frame rate (dt = 0.5”) Zenodo 1 (30’-PR) Zenodo 2 (30’-PR) Zenodo 3 (30’-PR) Zenodo 4 (30’-PR) Zenodo 5 (30’-PR) Zenodo 6 (100”-PR) Zenodo 7 (30’-PR) Zenodo 8 (30’-PR) Zenodo 9 (dt = 0.5") Zenodo 10 (30’-PR) Concatenated TIFFs and timestamp files for all of the 30’-PR data. Zenodo 11 (1/2) Zenodo 12 (2/2) Python pipeline to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell. ChroMag-pipeline repository Final registered and rotated TIFF files: 30’-PR experiments: n = 35 cells 100”-PR experiment, including time projections & kymograph dt = 0.5” experiments: n = 3 cells no force: n = 11 cells before manipulation, n = 8 cells after manipulation Data files with trajectories and force time profiles for all analyzed cells Instructions and Fiji/Python scripts to reproduce these files. Zenodo 13 Single-MNPs fluorescence: raw data, Python/Fiji scripts and instructions Zenodo 14 MagSim, Python library for magnetic simulations Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6). MagSim repository Force calibration – Method 1: Gradient of free GFP-ferritin in solution Raw microscopy data (6 pillars; Fig. S6B-C) Calculated force maps, with Fiji scripts and instructions to generate them. Zenodo 15 Force calibration – Method 2: Attraction of ferritin-coated beads (Fig. S7) Raw microscopy data (free diffusion and attraction) Python/Fiji scripts to calculate forces. Zenodo 16 Python library for force inference using different polymer models rouselib repository License: All the code, data and documentation in this repository is under GPLv3 license. The Author Accepted Manuscript of the study [Keizer et al. 2022] is under CC-BY 4.0 license. The Final Published Version, published by AAAS, is not (more information). Overview of the raw data repositories (Zenodo 1-10) Refer to the Material and Methods section of the article for details on data production. Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains: 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: The various positions were imaged before injection (folder with the _preInjection, _1-pre-inj or _1-inj_1 suffix) These positions were imaged again after injection (suffix _postInjection, _2-post-inj or _1-inj_2) and before the magnet was added (suffix _beforeexp or _before-attr) They were imaged again with the magnet added (suffix _attraction1). If acquisition was stopped and restarted an extra folder is created (suffix _attraction2) They were then imaged after the magnet was removed (suffix _release1) Finally, the cells were monitored after the experiment (suffix _after-exp or _postexp) A text file named lab_journal_[...].txt contains extra information the acquisition and experimental procedure Note: the MicroManager metadata in the TIFF file are fully populated Overview of the concatenated datasets (Zenodo 11-12) In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the ChroMag-pipeline repository. The folder contains: One TIFF file per selected position One .xls file per selected position, with one line per frame, and columns with the following information: path (Relative path): Reference to the original (raw MicroManager) file start_time (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed). time_in_file (seconds): Number of seconds between start_time and the acquisition of the current timepoint start_time_s (seconds): Variable start_time converted to a number of seconds time (seconds): Sum of start_time and time_in_file timestamp (Timestamp): Variable time, back-converted to a timestamp timeOn (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline timeOff (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline forceActivated (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff) seconds_since_first_magnet_ON (seconds): Number of (relative) seconds since the magnet was added for the first time. Frame (Integer) Frame number (1-indexed) Positions (Integer): The position number Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16) These datasets and their analysis are fully described in the Materials and Methods section of the article and in the different README.md files within the various folders of the datasets.

本数据集包含用于复现Keizer等人(2022)发表于《Science》第377卷第6605期论文《活细胞基因组位点显微操纵揭示间期染色质力学》（DOI: 10.1126/science.abi9810）中呈现结果所需的数据、软件与文档。 **描述** **存储位置** **集中式GitHub仓库**，包含以下内容：所有代码与轨迹/力文件的本地副本；用于生成Keizer等人论文中全部图表的Jupyter笔记本；指向本表格所列全部数据集的链接。Keizer等人相关仓库 **原始显微成像数据**：采用30’-PR方案开展的实验、采用100”-PR方案开展的实验、采用高帧率（dt = 0.5"）开展的实验，对应以下Zenodo（Zenodo）仓库： Zenodo 1（30’-PR）、Zenodo 2（30’-PR）、Zenodo 3（30’-PR）、Zenodo 4（30’-PR）、Zenodo 5（30’-PR）、Zenodo 6（100”-PR）、Zenodo 7（30’-PR）、Zenodo 8（30’-PR）、Zenodo 9（dt = 0.5"）、Zenodo 10（30’-PR）。上述仓库包含所有30’-PR数据的拼接TIFF（TIFF）文件与时间戳文件。 Zenodo 11（1/2）、Zenodo 12（2/2）：用于生成（i）拼接影像、（ii）针对每个细胞的裁剪旋转影像、（iii）针对每个细胞的力时间曲线的Python流程脚本，对应ChroMag-pipeline仓库。 **最终配准与旋转后的TIFF文件**： - 30’-PR实验：n=35个细胞 - 100”-PR实验（含时间投影与时间序列扫描图（kymograph）） - dt = 0.5"实验：n=3个细胞 - 无外力组：操作前n=11个细胞，操作后n=8个细胞包含所有分析细胞的轨迹与力时间剖面数据文件，以及复现这些文件所需的操作指南与Fiji（Fiji）/Python脚本，对应Zenodo 13。 **单磁纳米颗粒荧光数据**：原始数据、Python/Fiji脚本与操作指南，对应Zenodo 14。 **MagSim**：用于磁仿真的Python库，附带用于校准与生成映射图的Jupyter笔记本（对应补充图S5与S6），对应MagSim仓库。 **力校准——方法1**：溶液中游离GFP-铁蛋白的梯度分布。包含原始显微成像数据（6个微柱；补充图S6B-C）、计算得到的力映射图，以及生成这些映射图的Fiji脚本与操作指南，对应Zenodo 15。 **力校准——方法2**：铁蛋白包覆微球的吸引效应（补充图S7）。包含原始显微成像数据（自由扩散与吸引过程）、用于计算力的Python/Fiji脚本，对应Zenodo 16。 **用于多聚合物模型力推断的Python库**：rouselib仓库。 **许可协议**：本仓库内所有代码、数据与文档均采用GPLv3许可协议。本文的《作者接受稿》（Author Accepted Manuscript）[Keizer et al. 2022]采用CC-BY 4.0知识共享许可协议。由美国科学促进会（AAAS）出版的**最终正式版本**不适用此许可（更多信息详见原文）。 **原始数据仓库（Zenodo 1-10）概览**：请参阅论文的《材料与方法》章节了解数据生成的详细信息。每个Zenodo数据集代表一天的采集数据，包含未用于后续下游分析的数据。每个数据集包含： MicroManager（MicroManager）的原始文件夹架构（一个文件夹包含载玻片上的多个成像位点）。当外置磁铁的放置或移除导致对焦丢失时，采集会暂停并重新启动，每次都会创建新的MicroManager文件夹。例如： - 注射前对各个位点进行成像（文件夹后缀为`_preInjection`、`_1-pre-inj`或`_1-inj_1`） - 注射后、添加磁铁前，再次对这些位点进行成像（后缀为`_postInjection`、`_2-post-inj`或`_1-inj_2`以及`_beforeexp`或`_before-attr`） - 添加磁铁后再次成像（后缀为`_attraction1`）。若采集再次暂停重启，则会创建额外文件夹（后缀为`_attraction2`） - 移除磁铁后再次成像（后缀为`_release1`） - 实验结束后对细胞进行持续监测（后缀为`_after-exp`或`_postexp`）一个名为`lab_journal_[...].txt`的文本文件包含采集与实验流程的额外信息。注意：TIFF文件中的MicroManager元数据已完整填充。 **拼接数据集（Zenodo 11-12）概览**：在这些Zenodo仓库中，每个成像位点（采集自不同文件夹）通过ChroMag-pipeline仓库中的代码拼接为单条TIFF影像。该文件夹包含： - 每个选定成像位点对应的一个TIFF文件 - 每个选定成像位点对应的一个.xls文件，每行对应一帧，列包含以下信息： - "path"（相对路径）：指向原始（MicroManager）文件的参考路径 - "start_time"（时间戳）：MicroManager在启动采集（按下"acquire"按钮）时保存的时间戳 - "time_in_file"（秒）：`start_time`与当前时间点采集时刻之间的秒数 - "start_time_s"（秒）：转换为秒数的`start_time`变量 - "time"（秒）：`start_time`与`time_in_file`的和 - "timestamp"（时间戳）：转换回时间戳格式的`time`变量 - "timeOn"（时间戳）：添加磁铁的时刻。该时间戳可在GitHub仓库chromag-pipeline的`datasets.cfg`文件中获取 - "timeOff"（时间戳）：移除磁铁的时刻。该时间戳可在GitHub仓库chromag-pipeline的`datasets.cfg`文件中获取 - "forceActivated"（布尔值）：当前帧采集时磁铁是否处于激活状态（由`timeOn`与`timeOff`计算得到） - "seconds_since_first_magnet_ON"（秒）：首次激活磁铁以来的相对秒数 - "Frame"（整数）：帧编号（从1开始索引） - "Positions"（整数）：成像位点点位编号 **处理后数据集（Zenodo 13）与校准数据集（Zenodo 14-16）**：这些数据集及其分析方法已在论文的《材料与方法》章节以及数据集各文件夹内的不同README.md文件中进行了完整说明。

提供机构：

Zenodo

创建时间：

2022-05-01