Find common ancestors

The point of all this analysis is to answer one question: how am I related to this match? GDAT 4 gives you several complementary tools for finding the common ancestor behind a cluster of matches.

Prerequisite: most of these tools need family groups. Import your ancestor trees and run Settings → Recompute family groups first.

Approaches, from broad to specific

Shared surnames

Analysis → Surnames lists the ancestor surnames that appear across your matches' trees. Click a surname to see every match who carries it — a fast way to spot a candidate line. (Works on raw tree data; no recompute required.)

Family groups (MRCA analysis)

Analysis → MRCA groups your matches by the ancestral couple they share. Expand a group to see its members, their shared cM, and any side/MRCA notes. Recolor a group to track it across screens.

Triangulation

Analysis → Triangulation finds chromosome regions where three or more of your matches share overlapping DNA and are all in-common-with each other — strong evidence of a shared ancestor on a specific segment. Set Minimum group size (default 3) and click Run Triangulation.

Group Compare

Analysis → Group Compare lets you select one or more family groups (Ctrl/Shift-click) and see the same ancestral couple as recorded in each match's tree, side by side — useful for confirming everyone really descends from the same couple.

Ancestor trees & pedigree

Ancestors shows a match's full ahnentafel plus a drawn pedigree chart. Pair it with the segment tools to connect DNA to a specific line.

The Ancestors pedigree chart and grouped ahnentafel grid.

A practical loop

Cluster your matches to isolate a branch.
Check Surnames and MRCA for a candidate common couple.
Triangulate to confirm the branch shares real overlapping DNA.
Use Group Compare and Ancestors to verify the line in each tree.
When you're confident, confirm and document the MRCA.

False-positive regions matter here. Pile-up and centromere regions cause spurious shared segments. GDAT excludes your kit's false-positive regions from segment and triangulation views so they don't create phantom “common ancestors.”