Multi-omics is a rapidly growing field of study that combines various biological data types, such as genomics, transcriptomics, proteomics, epigenomics, and metabolomics, to understand complex biological systems holistically. Integrating different omics data provides a comprehensive view of the underlying biological processes, leading to a deeper understanding of disease mechanisms and potential therapeutic targets.
Multi-omics analysis has broad use cases across various fields, including precision medicine, drug discovery, biomarker prediction, and agriculture and crop improvement.
Persistent Multi-omics solution – Analyze, visualize and manage omics data on a scalable cloud platform
Our Multi-omics solution unlocks the power of omics technology, serving as an accelerator for scientific discovery and a tailored service provider for fulfilling the unique research needs of our partners and customers.
In today’s fast-paced research environment, scientists and clinicians must have access to powerful tools that can help them manage and analyze vast amounts of complex omics data with ease. Our multi-cloud-based offering is designed to meet this need, providing a robust solution that seamlessly integrates with existing systems and modules to enhance current capabilities.
Persistent provides clients with multi-omics data analysis and interpretation for application towards biomarker prediction, drug target identification and prioritization, patient stratification, and tailored solutions for unique research needs.
Pre-loaded automated pipelines
Quick launch our pre-designed workflows for RNAseq, DNAseq, scRNAseq, and multi-omics data analysis
Diverse omics workflow manager support
Support for Nextflow, Cromwell, Git or custom pipelines
Interactive dashboard and comprehensive reporting
Intuitively designed visualizations that can help in effective decision making
Manage large scale data
Simplified data handling with a robust framework for managing, processing, and integrating data
Some Relevant Use Cases:
Identify gene alterations and predict and rank target genes to aid in drug discovery
Classify patients into subgroups based on omics profiles
Comprehensive reports and dashboard to assist in clinical research
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