Cuevas Daniel A, Edwards Robert A
Computational Science Research Center, San Diego State University, San Diego, CA, USA.
Department of Computer Science, San Diego State University, San Diego, CA, USA.
Bioinformatics. 2017 Jun 15;33(12):1905-1906. doi: 10.1093/bioinformatics/btx084.
Bacterial growth curves are essential representations for characterizing bacteria metabolism within a variety of media compositions. Using high-throughput, spectrophotometers capable of processing tens of 96-well plates, quantitative phenotypic information can be easily integrated into the current data structures that describe a bacterial organism. The PMAnalyzer pipeline performs a growth curve analysis to parameterize the unique features occurring within microtiter wells containing specific growth media sources. We have expanded the pipeline capabilities and provide a user-friendly, online implementation of this automated pipeline. PMAnalyzer version 2.0 provides fast automatic growth curve parameter analysis, growth identification and high resolution figures of sample-replicate growth curves and several statistical analyses.
PMAnalyzer v2.0 can be found at https://edwards.sdsu.edu/pmanalyzer/ . Source code for the pipeline can be found on GitHub at https://github.com/dacuevas/PMAnalyzer . Source code for the online implementation can be found on GitHub at https://github.com/dacuevas/PMAnalyzerWeb .
Supplementary data are available at Bioinformatics online.
细菌生长曲线是表征各种培养基成分中细菌代谢的重要表现形式。使用能够处理数十个96孔板的高通量分光光度计，定量表型信息可以轻松整合到描述细菌生物体的当前数据结构中。PMAnalyzer管道进行生长曲线分析，以参数化包含特定生长培养基来源的微量滴定孔内出现的独特特征。我们扩展了管道功能，并提供了这个自动化管道的用户友好型在线实现。PMAnalyzer 2.0版本提供快速自动生长曲线参数分析、生长识别以及样本重复生长曲线的高分辨率图形和几种统计分析。
补充数据可在《生物信息学》在线获取。
