BioChemCalc
This tool provides a quick and intuitive way to perform Principal Component Analysis (PCA) on tabular data. It is designed especially for users working with biological or chemical datasets, but can be used for any numerical data with group labels. The input is processed using Z-score standardization, ensuring that all variables are on the same scale before applying PCA. The results are visualized as a PC1 vs PC2 scatter plot, and downloadable as an Excel file including PCA coordinates and explained variance.
Prepare a CSV file where each row is a sample and each column is a variable. The first column should contain the group label (e.g., "control", "mutant_A"), and the following columns should contain numerical features. Click "Select CSV" to upload your file, then "Start" to process it. Once completed, you'll see the PCA plot and a button to download the result in Excel format. If you're unsure about the format, you can download a sample CSV file here.