BMC Bioinformatics. 2013;14 Suppl 16(Suppl 16):S4. doi: 10.1186/1471-2105-14-S16-S4. Epub 2013 Oct 22.
High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images. Even fewer of them are designed to transform the phenotypic features measured from these images into discriminative profiles that can reveal biologically meaningful associations among the tested perturbations.
We present a fast and user-friendly software platform called "cellXpress" to segment cells, measure quantitative features of cellular phenotypes, construct discriminative profiles, and visualize the resulting cell masks and feature values. We have also developed a suite of library functions to load the extracted features for further customizable analysis and visualization under the R computing environment. We systematically compared the processing speed, cell segmentation accuracy, and phenotypic-profile clustering performance of cellXpress to other existing bioimage analysis software packages or algorithms. We found that cellXpress outperforms these existing tools on three different bioimage datasets. We estimate that cellXpress could finish processing a genome-wide gene knockdown image dataset in less than a day on a modern personal desktop computer.
The cellXpress platform is designed to make fast and efficient high-throughput phenotypic profiling more accessible to the wider biological research community. The cellXpress installation packages for 64-bit Windows and Linux, user manual, installation guide, and datasets used in this analysis can be downloaded freely from http://www.cellXpress.org.
高通量、基于图像的细胞对遗传或化学干扰的反应筛选会生成大量的细胞图像。需要进行自动化分析来量化和比较这些干扰的影响。然而,当前免费提供的生物图像分析软件工具中,很少有针对这些图像进行高效处理进行优化的工具。更少有专门用于将从这些图像中测量的表型特征转化为可区分的特征,从而揭示测试干扰之间具有生物学意义的关联的工具。
我们提出了一个快速且用户友好的软件平台,称为“cellXpress”,用于分割细胞、测量细胞表型的定量特征、构建可区分的特征,并可视化生成的细胞掩模和特征值。我们还开发了一套库函数,用于加载提取的特征,以便在 R 计算环境下进行进一步的可定制分析和可视化。我们系统地比较了 cellXpress 与其他现有的生物图像分析软件包或算法的处理速度、细胞分割准确性和表型特征聚类性能。我们发现,在三个不同的生物图像数据集上,cellXpress 优于这些现有工具。我们估计,cellXpress 可以在现代个人台式计算机上不到一天的时间内处理全基因组基因敲低图像数据集。
cellXpress 平台旨在使更快速、更高效的高通量表型分析更容易被更广泛的生物研究社区所接受。适用于 64 位 Windows 和 Linux 的 cellXpress 安装包、用户手册、安装指南以及本分析中使用的数据集可从 http://www.cellXpress.org 免费下载。