PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics.
PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics.
复制标题
DOI：
10.1186/s12859-016-1134-2
复制
发表时间：
2016-06-23
影响因子：
3
通讯作者：
Blomberg A
中科院分区：
文献类型：
--
作者：
Fernandez-Ricaud L;Kourtchenko O;Zackrisson M;Warringer J;Blomberg A
表型组学是功能基因组学的一个领域，它记录了生物体表型在遗传、表观遗传或环境背景下的大规模变异。对于微生物来说，关键的表型是种群规模的增长，因为它包含与适应性直接相关的信息。由于技术创新和广泛的自动化，我们记录复杂和动态微生物生长数据的能力迅速超过了我们解剖和可视化这些数据并提取其包含的健身组件的能力，阻碍了微生物学所有领域的进步。为了自动可视化，分析和探索复杂和高分辨率的微生物生长数据，以及标准化提取其包含的健身组件，我们开发了软件PRECOG（PREsentation and Characterization Of Growth-data）。PRECOG允许用户进行质量控制，与微生物生长数据进行交互和评估，轻松，快速和准确，即使在非标准生长动力学的情况下也是如此。质量指数从低质量的生长实验中过滤高质量的生长实验，减少误报。PRECOG中的预处理滤波器在计算上是廉价的，但在功能上可与更复杂的神经网络程序相媲美。我们提供的例子中，数据校准，项目设计和特征提取方法有一个明确的影响估计的生长性状，强调需要适当的标准化数据分析。PRECOG是一个工具，它简化了生长数据的预处理，表型性状提取，可视化，分布和创建巨大的和信息丰富的表型数据库。本文的在线版本（doi：10.1186/s12859-016-1134-2）包含补充材料，可供授权用户使用。
Phenomics is a field in functional genomics that records variation in organismal phenotypes in the genetic, epigenetic or environmental context at a massive scale. For microbes, the key phenotype is the growth in population size because it contains information that is directly linked to fitness. Due to technical innovations and extensive automation our capacity to record complex and dynamic microbial growth data is rapidly outpacing our capacity to dissect and visualize this data and extract the fitness components it contains, hampering progress in all fields of microbiology. To automate visualization, analysis and exploration of complex and highly resolved microbial growth data as well as standardized extraction of the fitness components it contains, we developed the software PRECOG (PREsentation and Characterization Of Growth-data). PRECOG allows the user to quality control, interact with and evaluate microbial growth data with ease, speed and accuracy, also in cases of non-standard growth dynamics. Quality indices filter high- from low-quality growth experiments, reducing false positives. The pre-processing filters in PRECOG are computationally inexpensive and yet functionally comparable to more complex neural network procedures. We provide examples where data calibration, project design and feature extraction methodologies have a clear impact on the estimated growth traits, emphasising the need for proper standardization in data analysis. PRECOG is a tool that streamlines growth data pre-processing, phenotypic trait extraction, visualization, distribution and the creation of vast and informative phenomics databases. The online version of this article (doi:10.1186/s12859-016-1134-2) contains supplementary material, which is available to authorized users.