Dimensionality Reduction

2D PCA

Interactive 2D principal component analysis visualization. Explore sample clustering and variance decomposition across hibernation states with publication-quality scatter plots.

Key Features

2D scatter plot

PC1 vs PC2 with confidence ellipses

Scree plot

Variance explained bar chart

Biplot overlay

Gene loading vectors on sample plot

Multi-group

Support for 10+ color-coded groups

Color Palette

Analysis Tip

Upload your gene expression matrix or analysis results in CSV/TSV format. The tool will automatically generate a publication-quality 2d pca figure ready for your hibernation omics manuscript.

Data Input

Upload Data

Drop TSV file here

Format: id | Type | feature1 | feature2 ...

Or paste data

Parameters

Clustering Method

Distance Metric

Scale

Color Scheme

2D PCA Visualization

Upload data and click "Generate 2D PCA" to visualize

Example Output

Input: Expression matrix (genes x samples)

Input Format

Gene expression matrix with genes as rows and samples as columns. Supports CSV, TSV, and tab-delimited text files.

Output: Clustered heatmap with dendrograms

Output Features

Hierarchical clustering dendrograms, color scale legend, gene/sample labels, and annotation tracks for group metadata.