A TWO-PHASE APPROACH TO FUZZY SYSTEM IDENTIFICATION

A two-phase approach to fuzzy system identification is proposed. The first phase produces a baseline design to identify a prototype fuzzy system for a target system from a collection of input-output data pairs. It uses two easily implemented clustering techniques: the subtractive clustering method and the fuzzy c-means (FCM) clustering algorithm. The second phase (fine tuning) is executed to adjust the parameters identified in the baseline design. This phase uses the steepest descent and recursive least-squares estimation methods. The proposed approach is validated by applying it to both a function approximation type of problem and a classification type of problem. An analysis of the learning behavior of the proposed approach for the two test problems is conducted for further confirmation.     

Multivariate Forecasting with BVARs and DSGE Models

In this paper I assess the ability of Bayesian vector autoregressions (BVARs) and dynamic stochastic general equilibrium (DSGE) models of different size to forecast comovements of major macroeconomic series in the euro area. Both approaches are compared to unrestricted VARs in terms of multivariate point and density forecast accuracy measures as well as event probabilities. The evidence suggests that BVARs and DSGE models produce accurate multivariate forecasts even for larger datasets. I also detect that BVARs are well calibrated for most events, while DSGE models are poorly calibrated for some. In sum, I conclude that both are useful tools to achieve parameter dimension reduction. Copyright © 2016 John Wiley & Sons, Ltd.     

Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of stage 3, in which we evaluated 1,536 SNPs in 4,574 individuals with prostate cancer (cases) and 4,164 controls. We followed up ten new association signals through genotyping in 51,311 samples in 30 studies from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. In addition to replicating previously reported loci, we identified seven new prostate cancer susceptibility loci on chromosomes 2p11, 3q23, 3q26, 5p12, 6p21, 12q13 and Xq12 (P = 4.0 × 10(-8) to P = 2.7 × 10(-24)). We also identified a SNP in TERT more strongly associated with PrCa than that previously reported. More than 40 PrCa susceptibility loci, explaining ～25% of the familial risk in this disease, have now been identified.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Genome-wide association identifies three new susceptibility loci for Paget's disease of bone

Paget's disease of bone (PDB) is a common disorder characterized by focal abnormalities of bone remodeling. We previously identified variants at the CSF1, OPTN and TNFRSF11A loci as risk factors for PDB by genome-wide association study. Here we extended this study, identified three new loci and confirmed their association with PDB in 2,215 affected individuals (cases) and 4,370 controls from seven independent populations. The new associations were with rs5742915 within PML on 15q24 (odds ratio (OR) = 1.34, P = 1.6 × 10(-14)), rs10498635 within RIN3 on 14q32 (OR = 1.44, P = 2.55 × 10(-11)) and rs4294134 within NUP205 on 7q33 (OR = 1.45, P = 8.45 × 10(-10)). Our data also confirmed the association of TM7SF4 (rs2458413, OR = 1.40, P = 7.38 × 10(-17)) with PDB. These seven loci explained ～13% of the familial risk of PDB. These studies provide new insights into the genetic architecture and pathophysiology of PDB.     

A genome-wide association scan identifies the hepatic cholesterol transporter ABCG8 as a susceptibility factor for human gallstone disease

With an overall prevalence of 10-20%, gallstone disease (cholelithiasis) represents one of the most frequent and economically relevant health problems of industrialized countries. We performed an association scan of >500,000 SNPs in 280 individuals with gallstones and 360 controls. A follow-up study of the 235 most significant SNPs in 1,105 affected individuals and 873 controls replicated the disease association of SNP A-1791411 in ABCG8 (allelic P value P(CCA) = 4.1 x 10(-9)), which was subsequently attributed to coding variant rs11887534 (D19H). Additional replication was achieved in 728 German (P = 2.8 x 10(-7)) and 167 Chilean subjects (P = 0.02). The overall odds ratio for D19H carriership was 2.2 (95% confidence interval: 1.8-2.6, P = 1.4 x 10(-14)) in the full German sample. Association was stronger in subjects with cholesterol gallstones (odds ratio = 3.3), suggesting that His19 might be associated with a more efficient transport of cholesterol into the bile.