Abstract
Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. It has become common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for scalable data management and easily accessible means of analysis.We present qPortal, a platform providing users with an intuitive way to manage and analyze quantitative biological data. The backend leverages a variety of concepts and technologies, such as relational databases, data stores, data models and means of data transfer, as well as front-end solutions to give users access to data management and easy-to-use analysis options. Users are empowered to conduct their experiments from the experimental design to the visualization of their results through the platform. Here, we illustrate the feature-rich portal by simulating a biomedical study based on publically available data. We demonstrate the software’s strength in supporting the entire project life cycle. The software supports the project design and registration, empowers users to do all-digital project management and finally provides means to perform analysis. We compare our approach to Galaxy, one of the most widely used scientific workflow and analysis platforms in computational biology. Application of both systems to a small case study shows the differences between a data-driven approach (qPortal) and a workflow-driven approach (Galaxy).qPortal, a one-stop-shop solution for biomedical projects offers up-to-date analysis pipelines, quality control workflows, and visualization tools. Through intensive user interactions, appropriate data models have been developed. These models build the foundation of our biological data management system and provide possibilities to annotate data, query metadata for statistics and future re-analysis on high-performance computing systems via coupling of workflow management systems. Integration of project and data management as well as workflow resources in one place present clear advantages over existing solutions.
Highlights
As the number of multi-omics projects especially in biomedical research is steadily increasing, the importance of digital management platforms that support the entire project and data life cycle is growing
Researchers try to centralize the coordination of these efforts on large-scale research consortia, the International Cancer Genome Consortium (ICGC) being a prominent example
In genomic research there are solutions such as Galaxy, which provide an open web-based platform and workflow system for analysis of genomic data [10]. Another web-based platform which provides analytical tools for gene expression, sequence variation, proteomic, and network analysis among others is GenePattern [11]. Such platforms can be augmented with additional data and metadata management strategies and converge into a Laboratory Information Management System (LIMS) [12] solution or even larger automated systems [13]
Summary
As the number of multi-omics projects especially in biomedical research is steadily increasing, the importance of digital management platforms that support the entire project and data life cycle is growing. Web-based solutions can bridge the gap between the different parties involved in scientific projects Such platforms are an established approach to provide scientists with a centralized interface to data, metadata and analysis tools that bring additional value to the project and solve aforementioned problems. Another web-based platform which provides analytical tools for gene expression, sequence variation, proteomic, and network analysis among others is GenePattern [11] Such platforms can be augmented with additional data and metadata management strategies and converge into a Laboratory Information Management System (LIMS) [12] solution or even larger automated systems [13]. The fundamental requirement for annotating new experimental data presented in web portals can drastically improve the means for sharing data with a wider scientific community This re-use provides possibilities for data mining and new big data approaches that benefit from more correlative power of leveraged data [19]. The aforementioned portal solutions indicate the large variety of served purposes, ranging from bioinformatics workflow management, management of different omics technologies to visualization applications, e.g. for cancer research
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