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Core Flow Concepts

Projects

Projects are the fundamental organizational unit in Flow, designed to group related biological experiments and their analyses. They provide a structured way to manage complex research efforts, from small pilot studies to large-scale collaborative projects.

What are Projects?

Projects in Flow serve as containers that bring together all the components of your research:

  • Samples: The biological specimens you're analyzing
  • Data: Raw sequencing files and analysis results
  • Executions: The computational analyses you've run
  • Metadata: Experimental details and documentation
  • Collaborators: Team members with access to the project

Think of projects as research folders that can grow and evolve with your work, maintaining a complete record of your scientific journey.

When to Create Projects

One Project Per Study

Most researchers create one project for each distinct research question or study:

  • Thesis chapters: Graduate students often create one project per chapter
  • Publications: Labs typically create one project per paper
  • Grant aims: Projects can align with specific grant objectives
  • Time-based studies: Longitudinal studies or time courses
  • Collaborations: Shared projects for multi-lab efforts

Examples of Project Organization

Small Study (5-10 samples):

"CRISPR Screen Validation"
├── 3 control samples
├── 3 knockout samples
└── 1 RNA-seq analysis

Medium Study (20-50 samples):

"Mouse Model Characterization"
├── Wild-type mice (n=10)
├── Mutant mice (n=10)
├── Multiple tissue types
├── RNA-seq + ChIP-seq analyses
└── Integrated analysis

Large Study (100+ samples):

"Clinical Trial Biomarkers"
├── Patient cohorts
├── Multiple time points
├── Various assay types
├── Batch processing
└── Statistical analyses

Project Components

Essential Information

Every project contains:

  1. Name: A clear, descriptive title
  2. Description: Detailed explanation of research goals
  3. Owner: The user who created the project
  4. Creation date: When the project was started
  5. Privacy settings: Who can access the project

Associated Resources

Projects link to:

  • Samples: All biological samples in the study
  • Pipelines: Analysis workflows used
  • Executions: Completed and running analyses
  • Results: Generated data and reports
  • Papers: Associated publications (when available)

Metadata Fields

Projects can store rich metadata:

  • Research objectives
  • Experimental design
  • Funding information
  • Publication status
  • External identifiers (GEO, SRA, etc.)
  • Custom fields for specific needs

Project Permissions

Flow provides flexible permission control for projects:

Permission Levels

  1. Admin: Full control over the project

    • Can delete the project
    • Manage all permissions
    • Modify all content

  2. Edit: Can modify project contents

    • Add/remove samples
    • Run analyses
    • Update metadata

  3. Analyze: Can run analyses only

    • Execute pipelines
    • View all data
    • Cannot modify structure

  4. View: Read-only access

    • See results and data
    • Download files
    • Cannot make changes

Sharing Strategies

Private Projects:

  • Only accessible to you
  • Ideal for preliminary work
  • Can be shared later

Group Projects:

  • Shared with specific lab members
  • Common for active research
  • Controlled collaboration

Public Projects:

  • Visible to all Flow users
  • Good for published data
  • Promotes reproducibility

Project Lifecycle

1. Planning Phase

Before creating a project, consider:

  • What samples will be included?
  • Which analyses will you run?
  • Who needs access?
  • How will results be organized?

2. Active Research

During active work:

  • Upload samples as they're generated
  • Run analyses iteratively
  • Document findings
  • Adjust organization as needed

3. Publication

When publishing:

  • Finalize all analyses
  • Document methods thoroughly
  • Create shareable links
  • Archive for long-term storage

4. Post-Publication

After publication:

  • Make data publicly accessible
  • Link to publications
  • Maintain for reproducibility
  • Respond to access requests

Best Practices

Naming Conventions

Use clear, informative names:

  • ✅ "2024_Smith_RNAseq_Cardiac_Development"
  • ✅ "CRISPR_Screen_Metabolic_Genes_Validation"
  • ❌ "Project1"
  • ❌ "Test"

Organization Tips

  1. Be consistent: Use similar structures across projects
  2. Document early: Add descriptions when memory is fresh
  3. Use subfolders: Organize complex projects with sample groups
  4. Tag appropriately: Use keywords for easy searching
  5. Regular cleanup: Archive completed projects

Collaboration Guidelines

  • Set permissions before inviting collaborators
  • Use project descriptions to communicate goals
  • Establish naming conventions with your team
  • Document analysis decisions
  • Regular progress updates

Advanced Features

Project Templates

Create reusable project structures:

  • Standard metadata fields
  • Common pipeline configurations
  • Preset sharing permissions
  • Organized folder hierarchies

Bulk Operations

Manage multiple items efficiently:

  • Upload many samples at once
  • Run pipelines on sample sets
  • Batch download results
  • Apply metadata to groups

Project Cloning

Duplicate existing projects:

  • Copy structure without data
  • Preserve configurations
  • Useful for similar studies
  • Template for new analyses

Integration Features

Connect with external systems:

  • Import from sequencing facilities
  • Export to repositories (GEO, SRA)
  • Link to lab notebooks
  • Connect to publication databases

Common Patterns

Multi-Omics Projects

Combining different data types:

"Stem Cell Differentiation Atlas"
├── RNA-seq (gene expression)
├── ATAC-seq (chromatin accessibility)
├── ChIP-seq (histone marks)
├── Proteomics data
└── Integrated analyses

Time Course Studies

Organizing temporal data:

"Circadian Rhythm Study"
├── Day 0 samples
├── Day 1 samples
├── Day 7 samples
├── Day 14 samples
└── Time-series analysis

Collaborative Projects

Multi-institution studies:

"Consortium Cancer Genomics"
├── Institution A samples
├── Institution B samples
├── Shared protocols
├── Combined analyses
└── Consortium results

Troubleshooting

Common Issues

Can't find a project?

  • Check your project list filters
  • Verify you have permission
  • Search by name or description
  • Contact project owner

Project is too large?

  • Archive old executions
  • Remove intermediate files
  • Use external storage for raw data
  • Split into sub-projects

Permissions not working?

  • Verify your role in the project
  • Check group memberships
  • Confirm with project admin
  • Review sharing settings

Next Steps

For more information about how projects fit into Flow's overall architecture, see the Core Concepts guide.

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