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GuidesExporting Results

Exporting Results

Export your Query Cards in multiple formats for presentations, publications, and data analysis.

Export Formats

High-resolution raster image suitable for:

  • PowerPoint/Keynote presentations
  • Posters
  • Quick sharing

Specifications:

  • Resolution: 300 DPI (publication quality)
  • Format: PNG with transparency
  • Size: Optimized for typical slide dimensions

Vector format for professional publications:

  • Infinitely scalable
  • Editable in Illustrator/Inkscape
  • Required by many journals

Best for:

  • Journal figures
  • Editing and customization
  • High-quality print

Complete Query Card data in JSON format:

  • Full statistical results
  • Raw data points
  • Query metadata
  • Reproducibility information

JSON export includes all data needed to recreate the analysis programmatically.

How to Export

  1. Click the Export button on your Query Card
  2. Select your desired format (PNG, SVG, or JSON)
  3. The file will download automatically

Export Contents

Figure Export (PNG/SVG)

The exported figure includes:

  • Main visualization (boxplot, bar chart, or Kaplan-Meier curve)
  • Axis labels and title
  • Statistical annotations (p-value, sample sizes)
  • Legend (if applicable)

JSON Export Structure

{
  "id": "card_abc123",
  "created_at": "2024-01-15T10:30:00Z",
  "query": {
    "original": "Is DDR1 higher in KIRP vs KIRC?",
    "parsed": {
      "gene": "DDR1",
      "cancer_types": ["KIRP", "KIRC"],
      "analysis_type": "differential_expression"
    },
    "sql": "SELECT ..."
  },
  "results": {
    "answer": "DDR1 expression is significantly higher...",
    "statistics": {
      "p_value": 0.00032,
      "fold_change": 2.3,
      "effect_size": 0.85
    },
    "sample_sizes": {
      "KIRP": 290,
      "KIRC": 533
    }
  },
  "figure": {
    "type": "boxplot",
    "data": { ... }
  },
  "methods": "Gene expression data were obtained from..."
}

Using Exports

In Publications

  1. Export as SVG
  2. Open in Adobe Illustrator or Inkscape
  3. Adjust fonts, colors, or labels as needed
  4. Export as PDF or EPS per journal requirements

When modifying figures, ensure changes don’t misrepresent the data. Always include original statistical values.

In Presentations

  1. Export as PNG
  2. Insert directly into PowerPoint/Keynote
  3. Resize as needed (PNG is high resolution)

For Further Analysis

  1. Export as JSON
  2. Load in Python/R for additional analysis
  3. Use raw data for custom visualizations

Python example:

import json
 
with open('query_card.json') as f:
    card = json.load(f)
 
# Access statistics
p_value = card['results']['statistics']['p_value']
fold_change = card['results']['statistics']['fold_change']
 
# Access raw data for custom plotting
data = card['figure']['data']

Citation

When using BioQuery results in publications, please cite:

Analysis performed using BioQuery (https://bioquery.io ). Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects.

The Methods section of each Query Card provides grant-ready text you can use directly.

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