DNA matches are not a list of percentages — they are a puzzle of shared segments, mystery parents and trees that only make sense when drawn as a network. Match lists in testing sites sort by centimorgans; they do not show how three mid-range matches triangulate through an unnamed ancestor. Researchers bounce between browser tabs, scribbled trees and messaging apps. Hypotheses die in chat threads, and the next evening starts from zero. linkchart turns DNA match family networks into a working board: persons, events, addresses and even company labs linked beside your documentary tree. You visualise clusters, test parental hypotheses and keep the genetic and paper stories aligned.
Why a real link chart for dna match networks
Most people start this work with tools that were never designed for networks. Documents narrate. Spreadsheets tabulate. Whiteboards photograph poorly and refuse to scale. A dedicated DNA match family network approach treats every person, place, asset and event as a node — and every meaningful connection as an edge you can label, question and revise.
That shift matters because decisions in dna match networks are rarely about a single record. They are about patterns: who introduces whom, which address keeps appearing, which phone bridges two clusters, which event changed the shape of the network. linkchart exists so those patterns stay visible while you work, not only in the final slide.
Researchers looking for a DNA match family network, genetic genealogy chart or triangulation map need a flexible canvas beyond pedigree software. linkchart.art helps you visualise clusters, hypotheses and documentary ties together.
Who this map is for
Genetic genealogists connecting DNA match lists to documentary trees and unidentified parentage puzzles.
The signature move on the canvas: Cluster matches first, hypothesize a shared ancestor second, and only then weld clusters to paper-trail person cards.
What belongs on the map
Every DNA match family network gets noisy when the wrong things dominate the board. Prioritise these domain-specific anchors before decorative extras:
- DNA match individuals and cluster IDs
- Hypothesized ancestral couples
- Documented descendants linking clusters
- Geographies that explain endogamy or migration
Sample relationship labels
Prefer short, scannable edge text. Useful starters for this domain include: shares cM with, in cluster, hypothesized child of, documented descendant of, triangulates with, eliminated from.
Your first week on this canvas
Import or manually add your strongest matches and group them into clusters on the canvas. Do not force surnames yet. Midweek, attach one well-documented ancestor hypothesis to the largest cluster and test whether known descendants sit where expected. By weekend, write elimination notes on clusters that cannot fit. The map should show which genetic neighbourhood still lacks a documentary bridge. Document why each card earned its place so the dna match networks board does not drift into decoration. Before the week closes, freeze a viewer link for one outsider and capture their first three questions as backlog edges or notes.
What not to do
Do not assign parentage from a single modest cM match. Avoid publishing living match identities without consent. Never ignore endogamy that inflates shared DNA. Resist building a pretty tree that contradicts the cluster evidence just to satisfy a hoped-for surname. If an edge cannot be explained in one plain sentence, it is not ready for a briefing view of your dna match networks map.
What success looks like
A working genetic network makes the next documentary target obvious: which cluster needs a death record, which hypothesis died, and which living tester might unlock a generation. Mysteries shrink because contradictions stay visible. When someone new opens the dna match networks canvas, they should grasp the live question, the strongest links, and the next check within minutes. That is the operational definition of a successful DNA match family network on linkchart.
How to use linkchart for dna match networks
You do not need a special template to begin. Open the linkchart app, create a map, and build outward from the question you must answer. The workflow below is a proven path for people doing dna match networks who want speed without losing structure.
- Create a map for the mystery you are solving — unknown parent, adoptee root, or cluster identity.
- Add your tested person and key matches as person cards with cM notes.
- Group matches into maternal/paternal clusters using labelled edges or spatial clusters.
- Link documentary parents and spouses only when evidence supports them; keep genetic-only links distinct.
- Attach birth, marriage and migration events that explain cluster geography.
- Invite a trusted research partner as editor when two heads beat one.
As the map grows, resist the urge to make it decorative. Beauty comes from clarity: consistent card titles, honest labels, and notes that explain uncertainty. A slightly ugly accurate chart beats a pretty misleading one every time — especially when dna match networks work has consequences.
Entity types that shine for this use case
linkchart supports investigation-ready cards you can reuse across domains. For dna match networks, start with these and expand only when a new type earns its place on the canvas:
Person Event Address Company Phone
Person and organisation cards carry identity. Addresses anchor geography. Phones and communication profiles expose bridges between clusters. Events give you time. Vehicles and items capture the physical world that dna match networks narratives often depend on. Together they form a vocabulary you can teach a teammate in minutes.
Real-world scenarios
Adoptee identifying a birth parent cluster
High matches refuse to answer messages, but their trees hint at a surname in one county. Person cards for responsive matches, address cards for that county, and event cards for a birth year window form a candidate cluster. An item card for a shared segment spreadsheet sits linked to the triangulation group. When a new match lands in the same cluster, the hypothesis strengthens without rebuilding a paper fan chart from scratch.
Surprise NPE in a surname study
Y-DNA and autosomal results disagree with the cherished paternal line. Mapping the paper line on one side and genetic clusters on the other keeps both truths visible. Event cards mark the generation where the paper edge should be treated as social parentage. Relatives can see why the study changed without feeling erased. Genetic-only edges stay visually distinct from documentary parentage until both stories can be reconciled. Living-match privacy rules govern what cousins may see when a collaborative viewer link goes out.
Endogamy muddles match strength
In a community with cousin marriage history, raw cM ranks mislead. Clustering matches by known documented lines on linkchart shows why a ‘close’ match is actually a web of smaller paths. Notes record which segments were truly triangulated. Research time shifts from chasing phantom grandparents to documenting the real mesh. Living-match privacy rules govern what cousins may see when a collaborative viewer link goes out. Centimorgan figures and testing-company tags on cards keep match lists comparable across evenings of research.
Across these scenarios the constant is the same: when dna match networks information stays trapped in siloed files, people argue about memory. When it lives as a labelled network, people argue about evidence — which is exactly where productive work happens.
Field practices that keep maps trustworthy
- Write cM and platform on the person card so lists stay comparable.
- Never merge matches into one card until identity is solid.
- Use hypothesis labels like possible parent cluster freely — genetics is iterative.
- Respect living matches’ privacy when sharing maps beyond your household.
Common pitfalls
- Do not assume the highest match is the most genealogically informative.
- Avoid publishing other people’s DNA details on public canvases.
- Resist forcing genetic edges to match a cherished paper surname.
Compared with slides, whiteboards and generic diagram tools
Slide software is excellent for presenting a finished argument and poor at hosting an evolving network. Whiteboards are wonderful for a one-hour workshop and hostile to long-running dna match networks work. Generic diagrammers can draw boxes and arrows, yet they rarely treat investigative entities as structured records with fields your team actually fills in. linkchart sits in the gap: fast enough for a working session, structured enough for a case file, visual enough for a briefing.
FAQ: DNA match networks
Does linkchart analyse raw DNA files?
No. Use your testing platforms and chromosome tools for science; use linkchart to organise people, clusters and documentary links.
Can I map matches from multiple companies?
Yes. Note the company on each person card and link cross-platform same person edges when verified.
How do I show triangulation?
Create a small cluster of matches sharing a segment and link them with triangulates with, citing the segment in notes.
Is this helpful for genetic genealogy professionals?
Yes — client maps stay structured, and deliverables can be viewer links instead of static PDFs alone.
Related ways to use linkchart
Ready to build your own DNA match family network? Open linkchart, place your first cards, and let the network tell the story you have been trying to hold in your head.