Profiler

Genedata Profiler® is designed to standardize and automate the integration of data from both internal and external sources. It facilitates the creation of tailored data products for effective analysis and secure collaboration. The platform serves as a single source of truth, managing all data types securely and efficiently, from raw files to analysis-ready datasets and reports.

Users can import data from various external file systems or federate public and proprietary databases, including LIMS and sample management systems. This ensures that the right data is accessible to the right person at the right time, enhancing data discoverability and usability.

Data Security and Collaboration

Genedata Profiler ensures data security, allowing for controlled sharing within teams or with external partners like CROs. Sensitive data assets remain secure with access controls in place.

Efficient Data Processing

The platform automates the processing and quality control of high-dimensional raw data such as NGS, digital pathology, and mass spectrometry. It streamlines complex analysis pipelines with ready-to-use workflows or custom workflows, enabling the analysis of hundreds of samples in hours.

Integrated Datasets

Genedata Profiler allows for the harmonization and integration of data across studies, combining multi-omics, biomarker, phenotype, and clinical data. Users can build application-specific data products without duplicating data for each consumer group, maintaining data security with fine-grained access controls.

Advanced Data Analysis and Visualization

The platform supports a wide range of advanced analyses, from summary statistics to machine learning, using its interactive tool, Analyst. Users can also connect to business intelligence services like Tableau and PowerBI for extended visualization. Flexible APIs allow integration with third-party analytical tools, ensuring data is securely managed.

Genedata Profiler is used in various research settings, aiding in the integration of biomarker data and supporting the development of personalized treatments. It is a reliable partner in big multi-omics data analysis, enhancing the capacity to analyze large datasets from translational and clinical research projects.