ProCogia analyzed and visualized spatially resolved single-cell sequencing data
Company Information
A leading Biotech company aimed to elevate its capabilities in single-cell sequencing analysis by developing a product that could analyze and visualize spatial transcriptomics data. This endeavor required a sophisticated computational framework that could handle the complexity of spatially resolved single-cell data. ProCogia was chosen for this project, leveraging its expertise in bioinformatics, R development, and data science to create a robust solution that would enable the client to commercialize a groundbreaking analytical product.
The Challenge
The project presented several challenges, including the refactoring of an existing codebase to support complex analysis algorithms efficiently, overcoming computational limitations inherent in single-cell data analysis, and ensuring the scientific accuracy of the analyses. Additionally, the solution needed to be user-friendly, scalable, and capable of integrating multi-modal data for comprehensive spatial transcriptomics analysis.
Procogia’s Approach
Our team of Bioinformaticians, R Developers, and Data Scientists was led by a Project Manager who collaborated with the client to ensure scientific accuracy, efficient user-friendly code, and timely delivery of this end-to-end project.
Drawing on our R for Life Sciences expertise, we built a robust computational framework to analyze and visualize spatial transcriptomic data. This will enable the client to commercialize a product that is the next step in single-cell sequencing analysis.
We designed and implemented the pipeline framework by refactoring an existing code base for efficient and complete execution of complex analysis algorithms. A script-based pipeline was built into a single R package for ease of use and scalability.
AWS products, including S3 buckets and Amazon Elastic Kubernetes, were used during the testing and hosting of the pipeline framework to overcome computational limitations when dealing with complex single cell data samples.
The Results
The framework allows for complex data analysis and efficient integration of multi-modal data.
Memory requirements are reduced, and R Shiny applications accelerate rendering of visualizations.
Algorithms used in the analysis pipeline are optimized to ensure robust scientific accuracy.
Services Used
Data Consultancy
We provide Data Consultancy to organizations to optimize your investment in people, processes, and technology.
Data Science
Using a blend of mathematics, software tools, business intelligence, and algorithms, we can draw insights and patterns from your raw data, allowing you to make intelligent data-driven decisions.
Bioinformatics
We deliver scientific results that drive clinical and translational research decisions. Our Bioinformatics team has extensive experience designing, optimizing, executing and analyzing pre-clinical and clinical research projects using next-generation sequencing technologies.
Conclusion
ProCogia’s development of a computational framework for analyzing and visualizing spatially resolved single-cell sequencing data represents a leap forward in the field of bioinformatics. By enabling the Biotech company to commercialize a product that advances single-cell sequencing analysis, ProCogia has contributed to the acceleration of scientific discovery and the potential for new insights into cellular function and disease mechanisms. This case study highlights ProCogia’s ability to translate complex biological data into actionable insights, driving innovation and enhancing the capabilities of its clients in the life sciences sector.
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