AutoSegment

AutoSegmenttm is a DNA segment-based clustering method that is available for segment data from MyHeritage, 23andme, FamilyTreeDNA and GEDmatch!
  • Requires segment data downloaded from testing companies
  • Does not require credential information

How to start an AutoSegment on Genetic Affairs



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AutoSegment intro

Up until now, the clustering methods for DNA matches provided by Genetic Affairs are based on the analysis of shared matches. However, using DNA segment data provided by the 4 companies, we can look for overlapping segments and thereby find groups of matches that share a segment. Since this method employs locally downloaded files, there is no need for your login credentials, and therefore no scraping of the websites. However, since these segment data files are "flat", there is no way to determine which segments triangulate. Meaning that before you dive into analyzing these clusters, users are strongly advised to perform follow up analyses on each of the clusters.

AutoSegment intro

Up until now, the clustering methods for DNA matches provided by Genetic Affairs are based on the analysis of shared matches. However, using DNA segment data provided by the 4 companies, we can look for overlapping segments and thereby find groups of matches that share a segment. Since this method employs locally downloaded files, there is no need for your login credentials, and therefore no scraping of the websites. However, since these segment data files are "flat", there is no way to determine which segments triangulate. Meaning that before you dive into analyzing these clusters, users are strongly advised to perform follow up analyses on each of the clusters.

Hybrid AutoSegment

Using the overlapping segments from MyHeritage, FamilyTreeDNA, 23andme and GEDmatch it is now possible to perform a hybrid clustering using all four datasets. This allows the analysis of all four companies in one clustering analysis.

Click here to start a hybrid analysis.

Hybrid AutoSegment

Using the overlapping segments from MyHeritage, FamilyTreeDNA, 23andme and GEDmatch it is now possible to perform a hybrid clustering using all four datasets. This allows the analysis of all four companies in one clustering analysis.

Click here to start a hybrid analysis.

AutoSegment concepts

Up until now, the clustering methods for DNA matches provided by Genetic Affairs are based on the analysis of shared matches. However, using DNA segment data provided by the 4 companies, we can look for overlapping segments and thereby find groups of matches that share a segment. Since this method employs locally downloaded files, there is no need for your login credentials, and therefore no scraping of the websites. However, since these segment data files are "flat", there is no way to determine which segments triangulate. Meaning that before you dive into analyzing these clusters, users are strongly advised to perform follow up analyses on each of the clusters.

AutoSegment concepts

Up until now, the clustering methods for DNA matches provided by Genetic Affairs are based on the analysis of shared matches. However, using DNA segment data provided by the 4 companies, we can look for overlapping segments and thereby find groups of matches that share a segment. Since this method employs locally downloaded files, there is no need for your login credentials, and therefore no scraping of the websites. However, since these segment data files are "flat", there is no way to determine which segments triangulate. Meaning that before you dive into analyzing these clusters, users are strongly advised to perform follow up analyses on each of the clusters.

Annotated AutoCluster clusters

Another potential issue of AutoSegment is the fact that large clusters can emerge from pile-up segments. Users can filter their segments using the known pile-up regions derived from the study of Li et al 2014. In addition, based on the imported segments a personal pile-up visualization is created that plots the occurrence of these segments on your chromosomes, thereby allowing you to identify personal pile-up regions.

Analysis of AutoSegment clusters

Another potential issue of AutoSegment is the fact that large clusters can emerge from pile-up segments. Users can filter their segments using the known pile-up regions derived from the study of Li et al 2014. In addition, based on the imported segments a personal pile-up visualization is created that plots the occurrence of these segments on your chromosomes, thereby allowing you to identify personal pile-up regions.

Known and personal pile-up regions

Another potential issue of AutoSegment is the fact that large clusters can emerge from pile-up segments. Users can filter their segments using the known pile-up regions derived from the study of Li et al 2014. In addition, based on the imported segments a personal pile-up visualization is created that plots the occurrence of these segments on your chromosomes, thereby allowing you to identify personal pile-up regions.

Known and personal pile-up regions

Another potential issue of AutoSegment is the fact that large clusters can emerge from pile-up segments. Users can filter their segments using the known pile-up regions derived from the study of Li et al 2014. In addition, based on the imported segments a personal pile-up visualization is created that plots the occurrence of these segments on your chromosomes, thereby allowing you to identify personal pile-up regions.

Analysis of AutoSegment clusters

Analysis of the segment based clusters is similar to the analysis of shared match clusters. In addition, because of the shared segment nature of these clusters, the identified clusters are also excellent candidates for cluster auto painter feature from DNA Painter.

Analysis of AutoSegment clusters

Analysis of the segment based clusters is similar to the analysis of shared match clusters. In addition, because of the shared segment nature of these clusters, the identified clusters are also excellent candidates for cluster auto painter feature from DNA Painter.

Results in Excel file

In some cases, especially when using low minimum cM values, the charts become quite large and difficult to interpret on the screen. An Excel file is therefore provided that contains the clusters as well.

Results in Excel file

In some cases, especially when using low minimum cM values, the charts become quite large and difficult to interpret on the screen. An Excel file is therefore provided that contains the clusters as well.

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