Freebase is a very large open knowledge database, which is generated in the form of community contributions, like Wikipedia. The idea of Freebase was first launched in 2000 by researchers in the field of web data, based on the concept of "knowledge web". Until 2010, Freebase was managed by Metaweb and the amount of data had reached 20 million topics. Appreciate the importance of this new approach, Freebase had been acquired by Google in June 2010 and continues to be developed so far. Based on the concepts of web data objects, information extraction is performed via Freebase APIs through HTTP protocol. This approach meets the requirements of common data query, however the downside is that it does not allow customizing the output for each user, or each application that needs to query on Freebase. In this paper, we propose a new approach to query Freebase data, which has the ability to customize the output for each user. Briefly, the system allows users to keep a desired graph which we call user's preference graph. Next, we use the APIs to query Freebase data. The difference here is that instead of returning the results to the user as the conventional Freebase API model, the system will use user's graph to adjust the query results, or continue to perform new queries. This process will be conducted repeated several times to achieve the target to search data in accordance with the wishes of the user.

MOTIVATION: Long expansions of short tandem repeats (STRs), i.e. DNA repeats of 2-6 nt, are associated with some genetic diseases. Cost-efficient high-throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads. RESULTS: We propose ab initio procedures for sensing and locating long STRs promptly by using the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in 11 SCA31 samples using SMRT(TM) sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads. AVAILABILITY AND IMPLEMENTATION: Our TRhist software is available at http://trhist.gi.k.u-tokyo.ac.jp/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.