Order DNA Matches by:
The rule based AutoCluster allows users to filter and/or merge their matches using matches from other profiles. Three different rules allow for the exclusion (NOT rule), inclusion (AND rule) or combination (OR rule) of matches. The resulting matches are used for an AutoCluster analysis. The use of these rules allow for a focus on matches from a particular branch of the family, for instance paternal or maternal matches. The usage of these rules is illustrated using the following family tree and an explanation of each of the three rules. Note that it is possible to combine different rules. First the AND and NOT rules are processed and used to filter the OR rules.
||NOT (or except) rule. In this scenario C is a person with an unknown parentage to her birth family (for instance adoptees or donor conceived persons) that has matches of her biological mother F. By applying the NOT rule on the matches of her biological mother F, the AutoCluster analysis is performed without her maternal matches. By using this strategy she can focus on her paternal matches to identify her biological father E.|
|AND (or intersection) rule. In this scenario B is a person with an unknown parentage to her birth family (for instance adoptees or donor conceived persons) that has identified a half-sister (C). By applying the AND rule, only paternal matches that are in common with her half sister are used for the AutoCluster analysis. This allows them to focus on the identification of their shared biological father E.|
OR (or union) rule. In this scenario two persons (A and B) with an unknown parentage to their birth families (for instance adoptees or donor conceived persons) would like to combine their matches (and shared matches) to identify one or both biological parents. If the biological mother already is known and tested, we can add another NOT rule rule which will exclude the matches of the biological mother D. Or if another half sister C and her biological mother F are known, we could add an OR rule to include the matches of C and a NOT rule to exclude the matches of F.
This approach especially enables donor conceived persons that have identified a large number of half brothers/sisters to combine all of their matches (using the OR rules) and remove the matches of their biological mothers (using the NOT rule). By employing this strategy, the majority of the paternal matches will be retrieved and used for clustering.
AutoCluster organizes your matches into shared match clusters that likely represent branches of your family. Each of the colored cells represents an intersection between two of your matches, meaning, they both match you and each other. These cells in turn are grouped together both physically and by color to create a powerful visual chart of your shared matches clusters. * *
Each color represents one shared match cluster. Members of a cluster match you and most or all of the other cluster members. Everyone in a cluster will likely be on the same ancestral line, although the MRCA between any of the matches and between you and any match may vary. The generational level of the clusters may vary as well. One may be your paternal grandmother’s branch, another may be your paternal grandfather’s father’s branch.
You may see several gray cells that do not belong to any color-grouped cluster. They usually represent a shared match where one of the two cousins is too closely related to you to belong to just one cluster. Each of these cousins belongs to a color-grouped cluster, the gray cell indicates that one of them belongs in both clusters. Unfortunately, the underlying code does not support multiple cluster membership.
It is possible to combine or exclude matches from several profiles for the same testing company using the rule based AutoCluster analysis. An added shared match link is illustrated with a plus symbol in te visualization. In addition, a plus symbol will also be added in the diagonal of the visualization if the match itself was not present in the original matchlist.
* * For more information on match clustering, see Bettinger, Blaine T. “Clustering Shared Matches,” The Genetic Genealogist, 3 January 2017.