docs/shiny_user_guide.md

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title: User Guide
parent: Shiny App
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Shiny App User Guide

Step-by-step instructions for using the Polyphenol Estimation Pipeline Shiny application.

Quick Start

1. Open the app (hosted version or run locally)
2. Go to the Input tab
3. Click Load Demo Data to try with sample data, or upload your own file
4. Click Run Pipeline
5. View results in the Results tab
6. Use Chart/Table buttons to switch between visualizations and data tables
7. Download results as CSV files

Data Requirements

ASA24 Data

Use the Items Analysis File from the ASA24 Researcher Site.

Required columns:

• UserName - Participant identifier
• FoodCode - WWEIA food code
• RecallNo - Recall number (1, 2, etc.)
• FoodAmt - Amount consumed in grams

Recommended columns for DII calculation:

• KCAL, PROT, TFAT, CARB, FIBE and other nutrient columns

Important: Each participant must have at least 2 completed recalls.

NHANES Data

Use the Individual Foods file from NHANES dietary data.

Required columns:

• SEQN - Participant sequence number
• DRXIFDCD - Food code
• RecallNo - Recall day

Recommended columns:

• DRXIGRMS - Amount consumed in grams
• DRXIKCAL, DRXIPROT, DRXITFAT and other nutrient columns

Using the Application

Step 1: Get Started Tab

The Get Started tab provides:

• Overview of what the pipeline does
• Three-step guide to using the app
• Pipeline workflow diagram

Click Go to Input to proceed.

Step 2: Input Tab

Select Data Source

Choose your data format:

• ASA24 for ASA24 Items files
• NHANES for NHANES Individual Foods files

Upload Data

Click the upload area or drag and drop your file. Accepted formats:

• CSV (.csv)
• Excel (.xlsx, .xls)

Click "Data format help" for column requirements.

The app validates your data and shows a preview on the right.

Or Load Demo Data

Click Load Demo Data to test with included sample ASA24 data.

Configure Options

• Include DII Calculation - Check to compute the 42-component Dietary Inflammatory Index

Step 3: Run Pipeline

Click Run Pipeline to process your data.

A progress indicator shows each step:

1. Preparing dietary data
2. Calculating nutrient totals
3. Disaggregating foods (FDA FDD)
4. Mapping to FooDB
5. Calculating polyphenol content
6. Summarizing total intake
7. Calculating class-level intake
8. Identifying food contributors
9. Calculating DII scores (if enabled)
10. Generating QA/QC report

The app navigates to Results when complete.

Step 4: View Results

Summary Cards

Four cards at the top show:

• Subjects Analyzed
• Mean Polyphenol Intake (mg/day)
• Polyphenol Classes
• Unmapped Foods

Results Tabs

Each tab has Chart and Table buttons in the header. Click to switch views.

Total Intake

• Bar chart: Mean intake by subject (top 30)
• Histogram: Distribution of intake across subjects
• Table: Subject-level values

By Polyphenol Class

• Bar chart: Mean intake by polyphenol class
• Table: Class-level breakdown per subject

Food Contributors

• Treemap: Top 50 foods by polyphenol contribution
• Table: Food contribution details

DII Scores (if enabled)

• Histogram: Distribution of DII scores
• Bar chart: Per-subject scores (green = anti-inflammatory, red = pro-inflammatory)
• Table: DII scores with all/no-alcohol variants

Step 5: QA/QC Tab

The QA/QC tab reports foods that could not be mapped to FooDB.

These items do not contribute to polyphenol estimates. Review the list to assess data quality.

Use Chart/Table buttons to switch between:

• Chart: Distribution of unmapped food percentage by recall
• Table: List of unmapped food items

Step 6: Download Results

Individual Downloads

Each results tab has a download button (download icon) to export that specific table.

Download All

Click Download All Results at the bottom of the Results tab to get a ZIP file containing:

File	Contents
total_intake_by_subject.csv	Mean polyphenol intake per subject
total_intake_by_recall.csv	Polyphenol intake per recall
class_intake_by_subject.csv	Class-level intake per subject
class_intake_by_recall.csv	Class-level intake per recall
food_contributors.csv	Food contribution rankings
dii_scores_by_subject.csv	DII scores per subject (if enabled)
dii_scores_by_recall.csv	DII scores per recall (if enabled)
unmapped_foods.csv	Foods not mapped to FooDB (if any)

Tips

• Test first: Use "Load Demo Data" to explore the app before uploading your data
• Check QA/QC: Review unmapped foods to understand data coverage
• Large files: Allow extra processing time for datasets with many subjects
• Reset: Click "Reset" to clear all data and start over
• Full screen: Click the expand icon on any card for full-screen view

About Page

The About tab contains:

• Pipeline methodology explanation
• Three-step process description
• Information about the 42-component DII calculation
• Credits for pipeline and application development
• Citation information for DII methodology