Why modern omics data projects need better workflow tools

In today’s fast-paced research and development environments, the ability to build, maintain and scale data processing workflows efficiently isn’t just a technical necessity - it’s a competitive advantage.

The hidden costs of traditional omics data workflows

Many organisations find themselves grappling with workflows that have grown organically over time, becoming increasingly difficult to maintain and adapt, risking faulty results or compliance issues. Common challenges include:

• Scripts that work on your computer but fail on other computers and platforms
• Issues with handling increasing data loads
• Hours spent managing software versions and dependencies
• Difficulty combining tools written in different programming languages
• Time lost debugging issues across complex pipelines

These aren’t just technical hurdles - they’re barriers that keep you from focusing on what really matters: your actual research and analysis.

Enter Viash: rethinking workflow development

Viash represents a paradigm shift in how data processing workflows are built and maintained. By introducing a component-based approach with automated code generation, Viash addresses the fundamental challenges that plague traditional workflow development. It’s designed both for technical teams who need granular control and managers and business stakeholders that need faster, more reliable results.

Key advantages:

• For technical teams: Gain the freedom to use any programming language, automate DevOps tasks and focus on actual data science instead of infrastructure management
• For team leads: Improve collaboration and accelerate project delivery with cleaner, more maintainable code
• For business stakeholders: lower maintenance costs, faster time-to-insight and improved return on investment from your data analysis initiatives

The following detailed comparison illustrates how Viash transforms common workflow development challenges into opportunities for improved efficiency and innovation.

Challenge	Pain Points in Traditional Workflows	Solution with Viash	Key Benefits of Viash Workflows
Adaptability and Maintenance	Over time, traditional pipelines tend to grow into monolithic blocks of code that are difficult to update or modify. Changes require extensive refactoring and risk breaking existing functionality, making maintenance increasingly challenging.	Viash enforces a modular architecture where components can be updated independently. Its configuration-driven approach separates analysis logic from infrastructure concerns, making maintenance straightforward and allowing seamless updates with evolving needs.	Easier updates Lower maintenance costs Faster iteration cycles Reduced technical debt
Polyglot support	Modern data analysis often requires combining tools written in different programming languages (e.g. Python, R or Bash). This typically leads to complex integration code and maintenance challenges, as teams spend valuable time writing and maintaining “glue code” instead of focusing on actual analysis work.	Viash provides native support for multiple programming languages and handles cross-language communication automatically through standardized module interfaces. Each tool’s requirements are neatly encapsulated, eliminating the need for manual integration work.	Use the best tool for each task Reduced integration complexity Reduced maintenance costs Faster development cycles
Reproducibility	One of the biggest challenges in traditional workflows is ensuring consistent results across different systems over time. As software versions change and computing environments vary, scripts often produce different results or fail entirely, making it difficult to validate analyses over time.	Viash takes care of reproducibility by automatically generating containers based on your specified dependencies. This ensures that your analysis runs in exactly the same environment everywhere, whether on a personal laptop, HPC environments or in the cloud.	Guaranteed consistent results Simplified compliance Reduced validation efforts Easy collaboration
Scalability	Traditional workflows often struggle when scaling from local development to cloud or HPC environments. This transition typically requires significant code changes and specialized expertise, creating bottlenecks and delays.	Viash seamlessly converts your scripts into Nextflow modules without requiring expertise in Nextflow’s DSL. The system handles asynchronous, distributed computing and execution environment management automatically, making scaling straightforward and efficient.	Seamless scaling to larger datasets Reduced infrastructure overhead Future-proof development No specialized expertise required
Testing & Debugging	In traditional pipelines, troubleshooting often requires running entire workflows to find errors. Problems can cascade through the system, making it extremely difficult to identify root causes and leading to lengthy debugging sessions.	Viash’s modular approach allows each component to be tested and debugged independently using built-in command-line tools. This isolation means issues can be identified and fixed quickly at the component level without affecting the rest of the pipeline.	Faster problem resolution Reduced downtime Improved reliability
Version management	As pipelines grow, keeping track of multiple script versions and their dependencies becomes increasingly complex. Updates to one component can unexpectedly break others, leading to instability and uncertainty about which versions were used for specific analyses.	Viash helps manage versions by keeping each module’s dependencies explicitly defined and isolated. While Viash doesn’t handle versioning automatically, its module structure makes it easier to track versions manually and ensures clear documentation of which dependencies were used for each analysis. With the upcoming release of Viash Hub in 2025, teams will get access to automated version tracking and management, ensuring clear traceability of which tool versions were used in each pipeline version.	Clear audit trails Safer updates Better risk management Reduced coordination overhead
Portability	Traditional workflows often face challenges when used across different platforms. System differences between operating systems and compute environments create recurring problems that require constant adjustments and custom fixes for each environment. This lack of portability makes maintaining consistent performance across diverse computing systems difficult and time-consuming.	Viash modules intelligently handle platform-specific differences behind the scenes, enabling your code to work seamlessly across Windows, Linux, macOS, HPC and cloud environments. The platform-agnostic architecture supports various containerization technologies including Docker, Podman and Singularity, while integrating diverse storage solutions such as cloud providers (e.g. google, AWS) and local file systems. This versatility allows developers to write code once and deploy anywhere, regardless of the underlying infrastructure.	Works everywhere out of the box Simplified deployment Reduced infrastructural maintenance Better collaboration across teams
Documentation	Documentation tends to become outdated as pipelines evolve, with setup instructions and dependency lists scattered across multiple locations. Sharing workflows with colleagues involves writing extensive setup guides, managing conflicting dependencies, and spending significant time on troubleshooting. This makes collaboration difficult and slows down knowledge transfer.	By keeping all module specifications, dependencies, and parameters in clear configuration files, Viash makes documentation an inherent part of development. These specifications serve as living documentation that’s always in sync with the actual code. Sharing becomes straightforward since modules are self-contained - colleagues can run them without complex setup procedures.	Always up-to-date documentation Effortless workflow sharing Faster team onboarding Clear component interfaces Better knowledge transfer Reduced support overhead

To learn more about how Viash works in practice, see our showcase article

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