i2d：一个用于模拟图像数据的 R 包及其在生物医学研究中的应用。
i2d: an R package for simulating data from images and the implications in biomedical research.
机构信息
Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA.
VA Connecticut Healthcare System, West Haven, CT 06516, USA.
出版信息
Bioinformatics. 2021 Aug 25;37(16):2497-2498. doi: 10.1093/bioinformatics/btaa991.
MOTIVATION
High-quality imaging analyses have been proposed to drive innovation in biomedical and biological research. However, the application of images remains underexploited because of the limited capacity of human vision and the challenges in extracting quantitative information from images. Computationally extracting quantitative information from images is critical to overcoming this limitation. Here, we present a novel R package, i2d, to simulate data from an image based on digital convolution.
RESULTS
The R package i2d allows users to transform an image into a simulated dataset that can be used to extract and analyze complex information in biomedical and biological research. The package also includes three novel and efficient methods for graph clustering based on simulated data, which can be used to dissect complex gene networks into sub-clusters that have similar biological functions.
AVAILABILITY AND IMPLEMENTATION
The code, the documentation, a tutorial and example data are available on an open source at: github.com/XiaoyuLiang/i2d.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
高质量的成像分析被提议用于推动生物医学和生物学研究的创新。然而，由于人类视觉的局限性和从图像中提取定量信息的挑战，图像的应用仍未得到充分利用。从图像中计算提取定量信息对于克服这一限制至关重要。在这里，我们提出了一个新的 R 包 i2d，用于基于数字卷积模拟图像数据。
结果
R 包 i2d 允许用户将图像转换为模拟数据集，可用于提取和分析生物医学和生物学研究中的复杂信息。该软件包还包含三种基于模拟数据的新颖高效的图聚类方法，可用于将复杂的基因网络分解为具有相似生物学功能的子簇。
可用性和实现
代码、文档、教程和示例数据可在开源网站上获得：github.com/XiaoyuLiang/i2d。
补充信息
补充数据可在生物信息学在线获得。
Zotero 插件