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SDP Overview
The Sylvester Data Portal (SDP) is a novel multi-omics research platform developed at the Sylvester Comprehensive Cancer Center. SDP facilitates the storage, management, analysis, and sharing of biomedical datasets. By leveraging state-of-the-art software and hybrid-cloud computing technologies, SDP provides researchers with well-annotated, FAIR (findable, accessible, interoperable, and reusable) and analysis-ready datasets, along with well-established bioinformatics tools and automated processing pipelines.
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Data Sources
The data sources for Sylvester Data Portal (SDP) are diverse and comprehensive, encompassing a wide range of biomedical and healthcare data types. As a multi-omics research platform, SDP aims to integrate and manage various datasets to facilitate advanced analysis and research.
RESEARCH DATA
Omics Data encompasses both Genomics Data and Transcriptomics Data. It includes a comprehensive set of biological data related to an individual's genetic makeup and gene expression patterns. Genomics Data involves DNA sequencing data, gene expression profiles, and genetic variations, providing insights into an individual's genetic information and identifying disease-causing mutations. On the other hand, Transcriptomics Data includes information about RNA expression levels and transcript sequences, offering valuable insights into gene expression patterns and regulatory mechanisms within cells or tissues. These omics data types are critical for advancing research in personalized medicine, disease understanding, and therapeutic development.
CLINICAL DATA
This includes patient information such as medical history, diagnosis, treatment records, and demographic details. Integrating clinical data with omics data allows researchers to correlate genomic variations with clinical outcomes.
Data Registration
Data registration is a crucial aspect of the Sylvester Data Portal that involves the systematic organization and standardization of metadata specifications for the datasets hosted within the platform. By employing standardized metadata, SDP enables global registration capabilities across Sylvester Comprehensive Cancer Center and fulfills data repository requirements, such as those set forth by the Gene Expression Omnibus (GEO).
Data Processing
Automated data processing is a critical component of the Sylvester Data Portal (SDP), designed to streamline the handling and analysis of complex biomedical datasets. Leveraging state-of-the-art technology, SDP employs well-established and frequently used data processing pipelines to deliver processed and well-annotated data, ready for further downstream analysis by researchers and scientists.
Integrated Storage
Integrated storage is a fundamental aspect of the SDP that facilitates the seamless organization and management of diverse biomedical datasets within a unified infrastructure. By employing standardized metadata specifications, SDP ensures that all data sources are harmonized and efficiently stored, enabling global registration capabilities across Sylvester Comprehensive Cancer Center and fulfilling data repository requirements, including those specified by the Gene Expression Omnibus (GEO).
Data Exploration
Intuitive data exploration is a key feature of the SDP that empowers researchers to seamlessly interact with their biomedical datasets. SDP provides a user-friendly and intuitive user interface (UI) that facilitates easy access, visualization, and exploration of complex data. Additionally, the platform offers well-documented Application Programming Interfaces (APIs) that support computational downstream analysis, enabling researchers to conduct in-depth investigations and extract valuable insights from their data.
Data Sharing
Effortless data sharing is a prominent feature of the Sylvester Data Portal that simplifies the process of securely sharing biomedical datasets among researchers and Sylvester Comprehensive Cancer Center resources. SDP employs a secure authentication system and a multi-level permission system, enabling seamless and controlled data sharing while maintaining data privacy and confidentiality.
