PheMaDB: A solution for storage, retrieval, and analysis of high throughput phenotype data

Background: OmniLog™ phenotype microarrays (PMs) have the capability to measure and compare the growth responses of biological samples upon exposure to hundreds of growth conditions such as different metabolites and antibiotics over a time course of hours to days. In order to manage the large amount of data produced from the OmniLog™ instrument, PheMaDB (Phenotype Microarray DataBase), a web-based relational database, was designed. PheMaDB enables efficient storage, retrieval and rapid analysis of the OmniLog™ PM data. Description: PheMaDB allows the user to quickly identify records of interest for data analysis by filtering with a hierarchical ordering of Project, Strain, Phenotype, Replicate, and Temperature. PheMaDB then provides various statistical analysis options to identify specific growth pattern characteristics of the experimental strains, such as: outlier analysis, negative controls analysis (signal/background calibration), bar plots, pearson’s correlation matrix, gr...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Wenling E. Chang, Keri Sarver, Brandon W. Higgs, Timothy D. Read, Nichole M. E. Nolan, Carol E. Chapman, Kimberly A. Bishop-Lilly, Shanmuga Sozhamannan
• Keywords: Artificial Intelligence, BMCBI 2011, OmniLog™ PM Data, Phenotype, Phenotype Microarray