MAV-seq – Management, Analysis and Visualization of Sequence Data

The increasing amount of heterogeneous Next Generation Sequencing (NGS) data generated today necessitates a robust platform for the efficient data storage, management, pre-processing, quality checking, analysis and visualization. Addressing each of these categories is a tremendous undertaking requiring high-level expertise from various disciplines. The typical genomic research laboratories do not always posses these resources, thus, researchers at the Jackson Laboratory have developed a scientific solution to assist researchers dealing with the practical issues associated to the high throughput genomic data. They present MAV-seq as a robust platform, which facilitates the management of samples metadata and NGS data pre-processing, quality assessment and visualization. MAV-seq provides interactive modular data flow, which transparently integrates interoperability, structure, standardization, security, controlled accessibility, management of genomic studies and their sample metadata associated with datasets of enormous size and diversity.

MAV-seq (Management, Analysis, Visualization of Sequence data) is an interactive, user friendly, cross platform, secure, encrypted, automated, customized, centralized, multi-roles based database application for the management of sample repertoires and automation of the data pre-processing of epigenomic and transcriptomic data. MAV-seq is a robust solution, which integrates different organizational units for efficient data sharing and communication. It supports, (i) management of research, experiment, sample and NGS metadata; (ii) controlled access to the centralized and distributed storage and high performance computing (HPC) resources for NGS data processing; (iii) interactive, automated and standardized quality checking, pre-processing and analysis of NGS data with visualization and report generation of obtained results; and (iv) partial integration with existing LIMS


Ahmed Z. (2016) MAV-seq: Management, Analysis and Visualization of Sequence Data. Nature Methods, [Application Note]

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