PCA GUI

Desktop GUI (Python/tkinter) for Principal Component Analysis on tabular data — e.g. compound/ metabolite concentration profiles across sample groups (HPLC data, chemotaxonomy, quality control), or any samples × variables dataset — producing publication-ready plots: scree plot, loadings bar chart and biplot.

Features

• Load data from Excel, in either orientation — samples as rows or samples as columns (with automatic transposition, see trasponi.py)
• Choose which variables to include and which samples to exclude, with per-group colors and distinct markers (up to 6 groups)
• Several scaling methods: z-score, mean-centering, min-max, robust, or none
• Automatic handling of missing values (mean imputation, with a warning)
• Three linked plots in one figure: scree plot (explained/cumulative variance), loadings bar chart, and biplot (scores + loading vectors + group confidence ellipses)
• Editable spreadsheet view of the loaded/transformed data
• Export: full figure or individual panels (PDF/PNG/SVG), scores/loadings/variance to Excel, or a ready-to-plot Excel workbook (separate sheets for scores, loading arrows, group ellipses) for building the same chart natively in Excel

Requirements

numpy, pandas, scikit-learn, matplotlib, openpyxl
adjustText   # optional — avoids overlapping labels in the biplot

See installa_pca_gui.txt for a step-by-step Windows/PowerShell setup guide (Italian).

Running

pythonw pca_gui.pyw

Double-clicking the .pyw file on Windows works too (no console window).

Input file formats

Standard layout — first row is the header, one sample per row:

Sample | Group | Variable1 | Variable2 | …
F1     | F     | 38.5      | 466.4     | …
F2     | F     | 0.03      | 370.7     | …

Transposed layout — samples arranged in columns, detected and converted automatically:

Samples  | F1   | F2   | … | SD6
Groups   | F    | F    | … | SD
Compound1| 38.5 | 0.03 | … | 0.07
Compound2| 466  | 370  | … | 240

trasponi.py converts a transposed file to the standard layout on its own (useful for sharing data with colleagues):

python trasponi.py <transposed_file.xlsx> [output_file.xlsx]

Structure

• pca_gui.pyw — main application (a single PCAApp class)
• trasponi.py — standalone converter, transposed layout → standard layout
• installa_pca_gui.txt — Windows setup guide (Italian)