Modern high-throughput genotyping techniques produce numerous missing calls that confound subsequent analyses, such as disease association studies. Common remedies or this problem include removing affected markers and/or samples or, otherwise, inferring the missing data. On small marker sets imputation is frequently based on a vote of the K-nearest-neighbor KNN) haplotypes, but this technique is neither practical nor ustifiable for large datasets.

We have developed a data structure called mismatch accumulator array (MAA) that supports efficient KNN queries over arbitrarily sized, sliding haplotype windows, and employ it for genotype imputation.

The performance of our method enables exhaustive exploration over all window sizes and known sites in large (150K, 8.3M) SNP panels. The graph below shows how’s NPUTE performance on 150 K SNPs with 46 Strains (65 ųs per imputation, ~7.5 minutes for the entire dataset).

Sami Says is an application designed to aid visually impaired children tell stories through sound. As an alternative to writing by hand, students are able to use Sami Says to record themselves speaking their stories aloud. All of the controls are implemented through simple keyboard commands and guided by text-to-speech. The students can choose from libraries of sound effects to insert into their story, so that they may better describe the characters and events. Teachers will be able to choose which sounds the students may use in a story, so that the children must find creative uses for the specific sounds as they write.

Sami Says exposes children to new technology and enables them to develop their creative writing abilities by creating something that would be difficult without this assistive technology. And they'll have fun, too.