Meta-Analysis Manuscript Assembly
Complete systematic review and meta-analysis manuscripts for journal submission by creating publication-ready tables, figures, and references.
When to Use
- Completing meta-analysis manuscript after analyses are done
- Creating tables from meta-analysis results
- Assembling multi-panel figures from forest/funnel plots
- Generating BibTeX references for systematic reviews
- Formatting manuscripts for high-impact journals (Lancet, JAMA, NEJM)
Prerequisites
Before using this skill, ensure you have:
- Completed meta-analyses with results tables (CSV format)
- Generated individual figures (PNG at 300 DPI)
- Manuscript text sections written (Abstract, Introduction, Methods, Results, Discussion)
- List of all citations needed
Workflow
Phase 1: Tables Creation
Create comprehensive tables from analysis results:
Main Text Tables
- Table 1: Trial Characteristics
- Extract from extraction.csv or similar - Include: NCT number, first author, year, design, sample sizes, intervention details, follow-up - Format as markdown with abbreviations section
- Table 2: Efficacy Outcomes Summary
- Combine results from all meta-analyses (pCR, survival outcomes) - Include: effect estimates, 95% CI, p-values, I², absolute benefits, NNT - Add GRADE certainty ratings
- Table 3: Safety Outcomes Summary
- From safety meta-analysis results - Include: adverse events, rates, RR/OR, NNH - Add clinical management guidance
Supplementary Tables
- Risk of Bias Assessment
- Use RoB 2 or ROBINS-I tool format - Domain-by-domain assessment for each trial - Overall risk rating with justifications
- GRADE Evidence Profile
- Summary of Findings table format - All outcomes with certainty ratings - Domain-specific justifications (bias, inconsistency, indirectness, imprecision)
- Detailed Results Tables
- Individual trial results - Subgroup analyses - Sensitivity analyses
Phase 2: Figure Assembly
Create multi-panel publication-ready figures:
Tool: Python Script with PIL/Pillow
# Create assemble_figures.py
from PIL import Image, ImageDraw, ImageFont
from pathlib import Path
def add_panel_label(img, label, position='top-left', font_size=80, offset=(40, 40)):
"""Add A, B, C labels to panels"""
draw = ImageDraw.Draw(img)
# Try to use system font
try:
font = ImageFont.truetype("/System/Library/Fonts/Helvetica.ttc", font_size)
except:
font = ImageFont.load_default()
x, y = offset
# Draw white background box for visibility
bbox = draw.textbbox((x, y), label, font=font)
padding = 10
draw.rectangle(
[bbox[0] - padding, bbox[1] - padding,
bbox[2] + padding, bbox[3] + padding],
fill='white',
outline='black',
width=2
)
draw.text((x, y), label, fill='black', font=font)
return img
def create_multi_panel_figure(images_list, output_path, labels=['A', 'B', 'C'], spacing=40):
"""Combine multiple images vertically with labels"""
# Add labels to images
labeled_images = [add_panel_label(img, label) for img, label in zip(images_list, labels)]
# Calculate dimensions
max_width = max(img.width for img in labeled_images)
total_height = sum(img.height for img in labeled_images) + spacing * (len(labeled_images) - 1)
# Create combined image
combined = Image.new('RGB', (max_width, total_height), 'white')
# Paste images
y_offset = 0
for img in labeled_images:
combined.paste(img, (0, y_offset))
y_offset += img.height + spacing
# Save at 300 DPI
combined.save(output_path, dpi=(300, 300))
return output_pathTypical Figure Structure
Main Text:
- Figure 1: Multi-panel efficacy (pCR, EFS, OS forest plots)
- Figure 2: Subgroup analysis (e.g., by biomarker status)
- Figure 3: Safety + Publication bias (SAE forest plot, funnel plot)
Supplementary:
- Supp Figure 1: Sensitivity analyses (leave-one-out plots)
- Supp Figure 2: Publication bias (funnel plots for all outcomes)
Phase 3: References Management
Create comprehensive BibTeX file:
Steps:
- Extract all citations from manuscript using grep
grep -E "¹|²|³|⁴|⁵|⁶|⁷|⁸|⁹|⁰|\[\d+\]" manuscript_sections.md - Create BibTeX entries for each reference
- Include DOI for all entries - Use standardized journal abbreviations (Index Medicus) - Format author names correctly
- Create mapping document
- Map superscripts (¹, ², ³) to BibTeX keys - Document citation locations in manuscript
- Create usage guide
- Pandoc conversion instructions - Zotero import instructions - Manual formatting examples (Lancet, JAMA style)
Phase 4: Figure Legends
Write comprehensive legends for all figures:
Legend Structure:
**Panel A. Outcome Name**
Description of what the panel shows. Forest plot showing [effect measure] for [outcome]
across [N] trials ([total participants]). [Statistical method used]. [Key result].
Horizontal lines represent 95% confidence intervals; diamond represents pooled effect.
Vertical line at [null value] indicates no treatment effect.
**Abbreviations**: List all abbreviations used.Include:
- Statistical methods (random-effects, Hartung-Knapp adjustment)
- Heterogeneity measures (I², Cochran's Q)
- Clinical interpretations
- Abbreviations definitions
Phase 5: Quality Assurance
Before submission, verify:
Tables
- All data matches analysis results exactly
- Abbreviations defined
- Footnotes explain all symbols
- Column/row headers clear
- Statistical notation consistent
Figures
- All figures at 300 DPI minimum
- Panel labels (A, B, C) visible and not obscuring data
- Legends match figures exactly
- Font sizes readable (≥8pt for final print size)
- Color schemes work in grayscale
References
- All citations have corresponding references
- Reference numbers sequential
- DOIs correct and working
- Journal abbreviations standardized
- Author names match original publications
Output Structure
07_manuscript/
├── tables/
│ ├── Table1_Trial_Characteristics.md
│ ├── Table2_Efficacy_Summary.md
│ ├── Table3_Safety_Summary.md
│ ├── SupplementaryTable1_RiskOfBias.md
│ ├── SupplementaryTable2_GRADE_Profile.md
│ └── ...
├── figures/
│ ├── Figure1_Efficacy.png (300 DPI)
│ ├── Figure2_Subgroup.png (300 DPI)
│ ├── Figure3_Safety.png (300 DPI)
│ ├── SupplementaryFigure1_Sensitivity.png
│ └── ...
├── references.bib
├── FIGURE_LEGENDS.md
├── CITATION_MAPPING.md
└── REFERENCES_USAGE_GUIDE.mdTime Estimates
- Tables creation: 2-3 hours
- Figure assembly: 1-2 hours
- References: 1-2 hours
- Legends: 1 hour
- QA: 1 hour
- Total: 6-9 hours
Journal-Specific Formatting
Lancet Oncology
- Word limit: 4000-5000 words
- Tables: 3-4 main text, unlimited supplementary
- Figures: 3-4 main text, unlimited supplementary
- References: Vancouver style, 30-40 typical
- Resolution: 300 DPI minimum
JAMA
- Word limit: 3500 words
- Tables: 4 max
- Figures: 4 max
- References: 40 max
- Resolution: 300-600 DPI
New England Journal of Medicine
- Word limit: 3000 words
- Tables: 3 max
- Figures: 3 max
- References: 40 max
- Resolution: 300 DPI minimum
Common Pitfalls to Avoid
- Tables: Don't mix effect measures (RR vs OR vs HR) without clear labeling
- Figures: Don't compress below 300 DPI
- References: Don't use auto-generated citations without verification
- Legends: Don't omit statistical methods or abbreviations
- Overall: Don't submit without independent verification of all numbers
Related Skills
/meta-analysis- Perform the statistical analyses/prisma-flow- Create PRISMA flow diagram/grade-assessment- Complete GRADE evidence profiles/risk-of-bias- Assess trial quality with RoB 2 tool
Example Invocation
/meta-manuscript-assemblyOr with specific phase:
/meta-manuscript-assembly tables
/meta-manuscript-assembly figures
/meta-manuscript-assembly referencesSuccess Criteria
- ✅ All tables publication-ready with comprehensive notes
- ✅ All figures 300 DPI with professional panel labels
- ✅ Complete BibTeX file with all 30-40 references
- ✅ Comprehensive figure legends
- ✅ All numbers verified against original analyses
- ✅ Manuscript follows target journal guidelines
- ✅ Ready for co-author review and submission