Research Project Management

Overview

Provides comprehensive project steering and management for bioinformatics research projects. Handles initialization, phase tracking, status monitoring, and best practices guidance.

Core Capabilities

1. Project Initialization

Initialize a new research project structure using scripts/init_project.py.

When to use: When starting a new research project or setting up a standardized structure.

Workflow:

1. Confirm project location (current directory or specified path)
2. Run initialization script from the plugin directory:

   python "${CLAUDE_PLUGIN_ROOT}/scripts/init_project.py" --path /path/to/target/project
   

   Important: Use ${CLAUDE_PLUGIN_ROOT} to reference the plugin's installation directory. The --path argument specifies where the project structure will be created.
3. Verify created structure
4. Guide user to next steps (edit STEERING.md, create first experiment)

Created structure:

project/
├── STEERING.md                             # Project progress tracker
├── notebook/
│   ├── tasks.md                            # Task management
│   ├── labnote/
│   │   ├── Exp00_TEMPLATE_labnote.ipynb    # Jupyter template
│   │   └── Exp00_TEMPLATE_labnote.md       # Markdown template
│   ├── report/
│   │   └── Exp00_TEMPLATE_report.md        # Report template
│   └── knowledge/                          # Reusable procedures
├── inbox/                                  # User input files
│   └── archive/                            # Processed files
├── data/raw/                               # Raw data (gitignored)
└── results/                                # Outputs (gitignored)

Command: /research-init

2. Status Checking

Check current project status, phase, and next actions.

When to use: When user asks "what's the status?", "where are we?", or "what should I do next?"

Workflow:

1. Read STEERING.md for current phase and priorities
2. Read notebook/tasks.md for experiment progress
3. Summarize:
   • Current phase
   • Active experiments
   • Completed milestones
   • Next recommended actions

Command: /research-status

3. Phase Management

Guide transitions between research phases using references/phases.md.

Research phases:

• Planning: Define research questions and hypotheses
• Exploration: Initial data analysis and hypothesis refinement
• Execution: Systematic experimentation
• Integration: Synthesize results into reports
• Publication: Prepare manuscripts and documentation

When to use: When project reaches a natural transition point or user requests phase update.

Workflow:

1. Review current phase from STEERING.md
2. Check phase completion criteria from references/phases.md
3. If criteria met, suggest phase transition
4. Update STEERING.md with new phase and priorities

4. Best Practices Guidance

Provide research best practices from references/best-practices.md and references/quality-standards.md.

When to use: When user needs guidance on:

• Hypothesis formulation
• Experimental design
• Scientific writing
• Data interpretation
• Quality standards

Key principles:

• Hypothesis-driven: Always start with testable hypotheses
• Reproducibility: Document everything for reproducibility
• Fact/interpretation separation: Keep observations separate from conclusions
• Progressive disclosure: Structure information hierarchically

5. Content Review

Proactively review user-created content against quality standards.

When to use: When user presents:

• Draft reports or conclusions
• Lab notebook entries
• Any scientific claims or findings

Action: Review content against references/quality-standards.md checklist:

1. Fact vs. Interpretation Check:

   • Are observations (facts) clearly separated from interpretation?
   • Are claims properly qualified with uncertainty level?
   • Are conclusions supported by cited evidence?

2. Evidence Traceability Check:

   • Does each claim link to a notebook/figure/table?
   • Are statistics complete (test name, n, effect size, p-value)?
   • Are figure references valid and accessible?

3. Reproducibility Check:

   • Are methods detailed enough for replication?
   • Are software/data versions specified?
   • Are random seeds documented?

Output: Provide constructive feedback with specific improvement suggestions.

Example feedback:

### Review Feedback

**Fact/Interpretation Issues**:
- Line 23: "Gene X regulates pathway Y" - This is interpretation, not fact.
  Suggest: "Gene X expression correlated with pathway Y activity (r=0.85, p<0.01)"

**Missing Evidence Links**:
- Finding 2 has no figure reference. Add: "(Figure 2B, Exp03_analysis.ipynb)"

**Statistics Incomplete**:
- Effect size missing for differential expression claim. Add fold-change and CI.

Resources

scripts/

• init_project.py: Project initialization script (executable)

commands/

• research-init.md: Project initialization command (/research-init)
• research-status.md: Status checking command (/research-status)

references/

• phases.md: Detailed phase definitions and transition criteria
• best-practices.md: Hypothesis-driven research guidelines
• quality-standards.md: Scientific quality standards (fact/interpretation/conclusion separation)

Usage Notes

• Always confirm project path before initialization
• Check for existing files to avoid overwriting
• Guide users through post-initialization steps
• Proactively suggest phase transitions when criteria are met
• Reference best practices when users show uncertainty