Association of GWAS loci with PD in China

Genome-wide association studies (GWAS) have identified numerous single-nucleotide polymorphisms (SNPs) at four loci (SNCA, PARK16, LRRK2, BST1) that can modulate the risk of Parkinson's disease (PD). The strength of these associations has yet to be clarified in Mainland China. Ethnic specific effect is an important consideration in GWAS analysis. Using a case-control methodology, we genotyped multiple SNPs at these four loci to investigate their association with risk of PD in Mainland China. A total of 1,146 study subjects comprising 636 patients with PD and 510 unrelated healthy controls were recruited. The minor alleles at SNPs rs894278, rs1994090, rs2046932, rs4698412, and rs7304279 were found to be significantly higher in cases than in controls, while the minor alleles were found to significantly reduce the risk of developing PD at SNPs rs823128, rs823156, rs6532194, rs1191532, and rs16856139. These associations remained after taking into considerations the effects of age and gender. We showed that multiple SNPs at LRRK2 and SNCA increase risk of PD, while PARK16 SNPs are associated with a lower risk of PD in China. Our study findings will contribute to further research using GWAS-linked data and research on ethnic specific effect of common variants.

TA-RE: An Exchange Language for Mining Software Repositories

Software repositories have been getting a lot of attention from researchers in recent years. In order to analyze software repositories, it is necessary to first extract raw data from the version control and problem tracking systems. This poses two challenges: (1) extraction requires a non-trivial effort, and (2) the results depend on the heuristics used during extraction. These challenges burden researchers that are new to the community and make it difficult to benchmark software repository mining since it is almost impossible to reproduce experiments done by another team. In this paper we present the TA-RE corpus. TA-RE collects extracted data from software repositories in order to build a collection of projects that will simplify extraction process. Additionally the collection can be used for benchmarking. As the first step we propose an exchange language capable of making sharing and reusing data as simple as possible.