Basics of Flow

Flow is a comprehensive bioinformatics platform that makes it easy to analyze biological data at scale. Whether you're running a single RNA-seq analysis or managing data for an entire research institute, Flow provides the tools and infrastructure you need.

What is Flow?

Flow is a cloud-based platform that brings together everything you need for bioinformatics analysis:

Data Management: Upload, organize, and share your biological data
Pipeline Execution: Run state-of-the-art analysis pipelines with a few clicks
Results Visualization: Explore your results through interactive reports and visualizations
Collaboration: Share data and results with your team or the broader scientific community

Who uses Flow?

Flow is designed for:

Wet lab scientists who need to analyze sequencing data without command-line expertise
Bioinformaticians who want to standardize and scale their analysis workflows
Research groups looking for a centralized platform to manage their data
Core facilities that need to deliver consistent, reproducible analyses

Core Concepts Overview

Flow is built around five interconnected concepts that work together to enable seamless bioinformatics analysis:

Projects: Organize related samples and analyses
Samples: Represent biological specimens and their data
Data: The actual files used and generated
Pipelines: Pre-configured analysis workflows
Executions: Individual analysis runs with full tracking

For a detailed explanation of these concepts and how they relate to each other, see our comprehensive Core Concepts Guide.

The Flow Workflow

A typical analysis in Flow follows these steps:

1. Upload Your Data

Start by uploading your sequencing files. Flow supports:

Direct upload from your computer
Import from cloud storage (S3, Google Cloud)
Transfer from sequencing facilities

2. Organize into Projects and Samples

Create a project to organize your work, then create samples with appropriate metadata:

My RNA-seq Project/
├── Control Sample 1
│   ├── control1_R1.fastq.gz
│   └── control1_R2.fastq.gz
├── Control Sample 2
│   ├── control2_R1.fastq.gz
│   └── control2_R2.fastq.gz
└── Treatment Sample 1
    ├── treatment1_R1.fastq.gz
    └── treatment1_R2.fastq.gz

3. Select and Configure a Pipeline

Choose an appropriate pipeline for your data type:

Browse the pipeline catalog
Review the pipeline documentation
Configure parameters (or use sensible defaults)
Select which samples to process

4. Monitor Execution

Once launched, you can:

Track progress in real-time
View resource usage
Check quality control metrics
Get notified when complete

5. Explore Results

When the pipeline finishes:

View interactive quality reports
Download processed data
Share results with collaborators
Export figures for publications

Key Features

Reproducibility

Every analysis in Flow is fully reproducible:

Pipeline versions are tracked
Parameters are recorded
Software environments are containerized
You can re-run any analysis exactly

Collaboration

Flow makes it easy to work with others:

Share projects with specific users or groups
Control permissions (view-only, can run analyses, full access)
Track who did what and when
Comment on results and findings

Scalability

Flow scales with your needs:

Process one sample or thousands
Automatic resource allocation
Parallel processing for speed
No infrastructure to manage

Security

Your data is protected:

Encrypted storage and transmission
Fine-grained access controls
Audit trails for compliance
Regular backups

Getting Started

Ready to begin? Here's how to get started with Flow:

Create an account - Sign up for free
Upload your first dataset - Get your data into Flow
Run a pipeline - Analyze your data
Explore the results - Understand your outputs

For more detailed information about Flow's architecture and technical implementation, see the Architecture Guide.