
What Is Secondary Analysis?
Secondary analysis in genomics refers to the computational processes and bioinformatics workflows applied to raw sequencing data after initial primary analysis, which typically involves base calling and sequence alignment. The objective of secondary analysis is to extract meaningful biological insights by identifying genomic features such as variants (e.g., single nucleotide polymorphisms, insertions, deletions), structural variations, gene expression levels, and other clinically or scientifically relevant markers. Secondary analysis software empowers teams to extract novel insights from complex data, speeding discovery and collaboration, but requires robust data integration and deep domain expertise to overcome heterogeneity.
Why Secondary Analysis is Crucial for Your Organization
Effective secondary analysis isn't just a technical step—it's a strategic advantage. It allows organizations to extract maximum value from their data, accelerating research and development cycles.
Identify and validate novel drug targets, stratify patient populations for clinical trials based on genetic markers, and understand mechanisms of drug resistance.
Develop and validate highly accurate molecular diagnostic tests by building robust and reproducible variant calling and annotation pipelines.
Enable precision medicine by interpreting patient genomic data to guide clinical decisions, diagnose rare diseases, and predict disease risk.
Increase the value and utility of your data assets by processing and harmonizing large-scale genomic datasets, making them ready for cohort-level analysis and collaborative research.
The Common Challenges of Secondary Analysis
While essential, performing secondary analysis at scale presents significant hurdles:
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Massive Data Volumes: Genomic datasets are enormous, creating challenges for data storage, transfer, and processing.
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Computational Complexity: Analysis pipelines require immense computational power, which can be expensive and difficult to manage with on-premise infrastructure.
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Pipeline Management: Building, validating, and maintaining complex bioinformatics pipelines is a specialized and time-consuming task.
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Security and Compliance: Genomic data is sensitive. Ensuring it is managed in a secure, compliant environment (e.g., HIPAA, GDPR) is non-negotiable.
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Collaboration Barriers: Sharing large datasets and analysis results with collaborators across different organizations securely and efficiently is often difficult.
The DNAnexus Solution: Scalable, Secure, and Collaborative Secondary Analysis

Infinite Scalability
Our cloud-native platform provides on-demand access to virtually unlimited computational and storage resources. Say goodbye to infrastructure bottlenecks and focus on the science.

Industry-Leading Security
We provide a secure and compliant environment with unmatched data governance controls. DNAnexus helps you meet rigorous regulatory requirements, including HIPAA, GDPR, and GxP.

Seamless Collaboration
Securely share data, tools, and workflows with colleagues and external partners in a controlled, project-based environment. Our platform enables global collaboration without the need to move or copy sensitive data.

Multi-Omics Integration
DNAnexus is designed to handle diverse data types. Integrate genomics, transcriptomics, proteomics, and more in a single environment to uncover deeper biological insights.
Ready to Streamline Your Secondary Analysis?
Stop wrestling with infrastructure and start accelerating your discoveries. The DNAnexus platform empowers your team to perform robust, reproducible secondary analysis with unmatched efficiency and security.
Contact us today to learn how DNAnexus can help you turn your complex biological data into breakthrough insights.