Two of our project grant awardees – Kevin Arvai and Andrew Riha – have been working tirelessly to build two new web tools that can make use of your genetic data that’s stored in Open Humans in interesting ways. And their hard work has paid off: Kevin’s Imputer and Andrew’s Lineage are now available!

Imputer is designed to fill the gaps in your genetic testing data. Direct-To-Consumer companies like 23andMe usually genotype just a small fraction of your genome, focusing on generating a low-resolution snapshot across your whole genome. Genotype imputation fills in those gaps by looking at reference populations of many individuals who have been fully sequenced in a high resolution, using this data to predict how to fill the gaps in your own data set. Imputer is using the reference data from the 1000 Genomes Project to perform this gap-filling and deposits the filled-up data in your Open Humans account. Kevin also provides two Personal Data Notebooks that you can use to explore your newly imputed data set. If you want to explore the quality of the newly identified variants, you can use this quality control notebook. And if you’re interested to see where your genome falls within a two-dimensional graph of different populations from around the globe, this notebook allows you to explore how closely you relate to other people in the 1000 Genomes data.

Andrew’s Lineage brings some further tools and genetic genealogy methods to Open Humans.  If you have been tested by more than one Direct-To-Consumer genetic testing company, Lineage allows you to merge those different datasets into one large file, while also highlighting the variants that came out as different between those tests. You can also lift your files to a newer version of the human reference genome, which might be needed for using your data with other tools. Furthermore, Lineage brings a lot of interesting genetic genealogy tools: It allows you to compute how much shared DNA can be found between your own data and the genetic data of other individuals, using a genetic map. You can then create plots of the shared DNA between those two data sets, determine which genes are shared between them and even find discordant SNPs between the data sets.

Enjoy exploring your DNA!