Bioinformatics Institute, A*STAR, Singapore.
Biotechniques. 2011 Jul;51(1):49-50, 52-3. doi: 10.2144/000113704.
Automated microscopy enables in vivo studies in developmental biology over long periods of time. Time-lapse recordings in three or more dimensions to study the dynamics of developmental processes can produce huge data sets that extend into the terabyte range. However, depending on the available computational resources and software design, downstream processing of very large image data sets can become highly inefficient, if not impossible. To address the lack of available open source and commercial software tools to efficiently reorganize time-lapse data on a desktop computer with limited system resources, we developed TLM-Converter. The software either fragments oversized files or concatenates multiple files representing single time frames and saves the output files in open standard formats. Our application is undemanding on system resources as it does not require the whole data set to be loaded into the system memory. We tested our tool on time-lapse data sets of live Drosophila specimens recorded by laser scanning confocal microscopy. Image data reorganization dramatically enhances the productivity of time-lapse data processing and allows the use of downstream image analysis software that is unable to handle large data sets of ≥2 GB. In addition, saving the outputs in open standard image file formats enables data sharing between independently developed software tools.
自动化显微镜使在发育生物学中长期进行体内研究成为可能。对三维或更多维度的延时记录来研究发育过程的动态可以产生巨大的数据,这些数据扩展到了 TB 级别。然而,根据可用的计算资源和软件设计,对非常大的图像数据集进行下游处理可能会变得非常低效,如果不是不可能的话。为了解决缺乏可用的开源和商业软件工具来在具有有限系统资源的台式计算机上有效地重组延时数据的问题,我们开发了 TLM-Converter。该软件可以将过大的文件分割成碎片,或者将代表单个时间帧的多个文件连接起来,并将输出文件以开放标准格式保存。我们的应用程序对系统资源的要求不高,因为它不需要将整个数据集加载到系统内存中。我们在通过激光扫描共聚焦显微镜记录的活果蝇标本的延时数据集上测试了我们的工具。图像数据重组极大地提高了延时数据处理的效率,并允许使用无法处理大于等于 2GB 的大型数据集的下游图像分析软件。此外,将输出保存为开放标准图像文件格式,可在独立开发的软件工具之间实现数据共享。