AmtDB | PCA

Step 1: Load Samples

Database Samples

There are no samples selected from AmtDB.
You can select samples from the database browser.

User Samples

Step 2: Data Configuration & Grouping

Data Grouping Levels

Define how to group data. If both database and file are used, aligning columns here concatenates their data.

CSV File Settings

Raw Data (Individual Samples)
Aggregated Data (Frequencies/Counts)

Haplogroup Unification Settings

Load Preset:

Choose a preset list of haplogroups.

Unknown groups:

Choose how to handle haplogroups that are not in the list.

Target haplogroups

List separated by commas. Use '*' for paragroups (e.g., N*) and '~' for exclusion (e.g., R~1a).

Step 3: Preview Input Data

Step 4: PCA Analysis & Plots

Biplot Display Settings

X Axis:

Y Axis:

Label by:

Column used for text labels on the plot.

Color by:

Missing values will be grouped as 'N/A'

Shape by:

Missing values will be grouped as 'N/A'

Show Loadings

Show Sample Labels

Graph Template:

Color Palette:

Show Legend

Legend Position:

Scree Plot Settings

Show top N components (0 for all):

Graph Template:

Show explained variance

Variance Line Color:

Show cumulative explained variance

Cumulative Line Color:

Calculated using: Python v3.9.2 | scikit-learn v1.6.1 | pandas v2.3.3 | numpy v2.0.2 | Plotly v6.6.0

Beta Version: The PCA Tool is currently in beta. We highly value your feedback, so please let us know if you encounter any issues or have suggestions for improvements.

PCA Tool Beta