PanelCheck

Sensory panel performance analysis — original macOS app extended with a full R translation.

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Overview

PanelCheck is a sensory panel analysis tool originally developed as a macOS desktop application (Python 2.7 + wxPython). This repository extends the original with a full R translation of all key statistical analyses, enabling reproducible, scriptable panel performance evaluation in RStudio — no GUI required.

The example dataset Data_Bread.xlsx (8 assessors × 5 breads × 2 replicates × 10 attributes) is included and works with both the app and the R scripts.

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Repository Structure

PanelCheck/
├── README.md                   # This file
├── Data_Bread.xlsx             # Example sensory panel data
│
├── PanelCheck.app/             # Original macOS Python application (do not modify)
│   └── ...                     # Python 2.7 + wxPython GUI source
│
├── css/                        # Styling assets for the HTML report
│   ├── style.css
│   ├── header.html
│   └── external-links-js.html
│
└── R/                          # R translation of PanelCheck analyses
    ├── 00_load_data.R          # Data loading and validation
    ├── 01_panel_performance.R  # ANOVA-based panel performance stats
    ├── 02_profile_plots.R      # Profile plots per assessor per attribute
    ├── 03_mixed_model.R        # Mixed model ANOVA + Tukey HSD + variance components
    ├── 04_pca.R                # PCA consensus analysis (biplot, scree, loadings)
    ├── 05_fvalue_overview.R    # F-value overview plots across all attributes
    ├── 06_eggshell_plot.R      # Eggshell assessor performance plots
    ├── run_all.R               # Master script — runs all analyses on a dataset
    └── utils.R                 # Shared helper functions

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R Translation

The R/ folder contains a clean, modular reimplementation of all PanelCheck analyses. It is designed to be run in RStudio and prioritises reproducibility and readability over GUI interaction.

Quick Start

Install required packages (first time only):

install.packages(c("readxl", "dplyr", "tidyr", "purrr", "ggplot2",
                   "car", "lme4", "lmerTest", "emmeans", "multcomp",
                   "FactoMineR", "ggrepel"))

Run the full pipeline:

source("R/run_all.R")

Or run individual modules:

source("R/00_load_data.R")
data <- load_panel_data("Data_Bread.xlsx")

source("R/01_panel_performance.R")
perf <- panel_performance(data)

Input Data Format

Column	Type	Description
Assessor	character	Panelist ID (e.g., AS1, AS2)
Sample	character	Product/sample ID (e.g., Bread1)
Replicate	numeric	Replicate number (1, 2, …)
Attr1…N	numeric	Sensory attribute scores

Analyses

Script	Analysis
01_panel_performance.R	Descriptive stats · 2-way ANOVA · discrimination · repeatability · agreement
02_profile_plots.R	Per-assessor profiles vs. panel mean · spider chart
03_mixed_model.R	Mixed model ANOVA · Tukey HSD · variance components
04_pca.R	Consensus PCA biplot · scree plot · loadings
05_fvalue_overview.R	F-value heatmap/dotplot · p-value heatmap

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Original macOS App

Note: The original app requires macOS High Sierra or later and is not actively maintained. Windows users: download from panelcheck.com.

The app is archived in PanelCheck.app/. It is built on Python 2.7 and wxPython. All data-analysis features work as intended; miscellaneous features such as the About and Help sections may not function as expected.

Installation

1. Download this repository
2. Unzip and place the folder somewhere meaningful (not in Downloads)
3. First launch — use Finder to navigate to the folder, then cmd+click the icon and follow the prompt

Double-clicking will launch the app normally on subsequent runs.

A Minimal Example

Open Data_Bread.xlsx via File › Import › Excel… and match the Assessor, Sample, and Replicate columns. Then explore:

View	What it shows
Univariate › Profile plots	Individual vs. consensus scoring per attribute
Multivariate › Tucker-1	Assessor agreement across attributes
Consensus › PCA scores	Product similarity map
Overall › Overview Plot (F values)	F-value summary across all attributes

Export any plot using the disk icon at the bottom left of the plot panel.

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Attribution

Original PanelCheck application developed by CPHFOOD.

The R translation in this fork was developed with assistance from Claude Code (Anthropic), an AI-powered coding assistant.