Digital RNA-Seq Workflow

Status: ✅ Completed & Validated | Tech Stack: Nextflow, Docker, AWS

Problem Solved / Scientific Goal

The main objective was to create an end-to-end bioinformatics pipeline for Digital RNA-Seq analysis. The crucial challenge wasn't just analyzing the data, but doing so in a highly reproducible and scalable manner.

Traditionally, such workflows are fragmented between different Bash or R scripts that fail when executed outside their ideal environment (HPC/Cloud). The goal was to create a single, robust orchestration engine capable of managing complex dependencies, hardware-specific steps, and various data sources.

Architecture Implemented

The architecture is built around Nextflow, acting as the central workflow orchestrator (DAG). This allows:

  1. Modularity: Dividing the analysis into logical and reusable blocks (modules/). If a block fails, you know exactly where to intervene without recreating everything from scratch.
  2. Hybrid & Scalable Execution: Thanks to nextflow.config integration, the workflow can seamlessly adapt between local (HPC) and cloud (AWS Batch/Singularity) environments.
  3. Containerization: The use of Docker/Singularity ensures software dependencies are always correct, eliminating "it works on my PC but not in production" problems.

Results & Takeaways

  1. The Power of Orchestration: The main lesson is that scientific complexity must be managed by a robust workflow management technology (Nextflow) rather than relying on sequential scripts. Orchestration is the real added value.
  2. Workflow Resilience: I learned the importance of explicitly predicting and managing failures (fail recovery). A good workflow must have automatic retry mechanisms or clear signaling for every block.
  3. Resource Management (Cloud/HPC): It's crucial not only to know what to calculate but also how to optimize hardware resources (GPU acceleration, cluster type) and adapt the script to that specific environment.

Tech Stack & Tools Used

  • Nextflow Workflow Management
  • Docker/Singularity Containerization
    • AWS Batch, HPC (SLURM)
  • R/Python for Analysis
    • Bash Scripting

GitHub Repository

Check out the code: digitalrnaseq on GitHub