Managing the data

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use different types of sequencing assays (RNA-seq, ChIP-seq, Methyl-seq, etc) in their research projects, with increasing number of samples and variety of experimental designs. This creates a wealth of data that require standardized annotation, storage and management both at the sample and the analysis levels. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays, as well as proteomics and metabolomics data (Hernandez-de-Diego et al, 2014) . The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures. See below some explanative figures of the EMS.

STATegraEMS_1

Metadata Module structure in STATegra EMS. The Sample module stores information of biological conditions, biological replicates and the associated analytical samples. The analysis module contains all analysis steps from raw to processed data. Both samples and analyses are associated to one or more experiments within the Experiment module.

STATegraEMS_3

Example of the EMS Interface.

 

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