Issues in information integration of omics data: microarray meta-analysis for candidate marker and module detection and genotype calling incorporating family information

Nowadays, more and more high-throughput genomic data sets are publicly available; therefore, performing meta-analysis to combine results from independent studies becomes an essential approach to increase the statistical power, for example, in the detection of differentially expressed genes in microarray studies. In addition to meta-analysis, researchers also incorporate pathway or clinical information from external databases to perform integrative analysis. In this thesis, I will present three projects which encompass three types of integrative analysis. First, we perform a comprehensive comparative study to evaluate 12 microarray meta-analysis methods in simulation studies and real examples by using four quantitative criteria: detection capability, biological association, stability and robustness, and we propose a practical guideline for practitioners to choose the most appropriate meta-analysis method in real applications. Second, we develop a meta-clustering method to construct co-expressed modules from 11 major depressive disorder transcriptome datasets, incorporated with GWAS and pathway information from external databases. Third, we propose a computationally feasible algorithm to call genotypes with higher accuracy by considering family information from next generation sequencing data for two purposes: (1) to propose a new genotype calling algorithm for complex families, and (2) to extend our algorithm to incorporate external reference panels to analyze family-based sequence data with a small sample size. In conclusion, we develop several integrative methods for omics data analysis and the result improves public health significance for biomarker detection in biomedical research and provides insights to help understand the underlying disease mechanisms

The epidemiology of patients with pterygium in southern Taiwanese adults: The Chiayi survey

AbstractPurposeTo investigate patients with pterygium in different geographic regions and the associated risk factors in southern Taiwan.MethodsA clinical observation survey was conducted in Chiayi County, a rural area in southern Taiwan. The subjects aged 40 years and above underwent complete ocular examinations. Associated risks factors were evaluated, including gender, age, occupations, smoking, and geographical living regions by univariant and multivariant logistic regression analysis.ResultsA total of 2197 participants (790 male, 36.0%) from 44 different villages were evaluated. In these, 554 participants (25.2%) have either unilateral or bilateral pterygium. Age is associated with the percentage of pterygium, and those aged between 60 and 69 had the highest percentage of 30.1% (p < 0.0001). The gender effect was higher among men than women (OR = 1.31, 95% CI: 1.08–1.60, p = 0.006). The percentage of pterygium lived in plain, seaside, and mountainous areas were 22.6%, 32.6%, and 14.5% respectively. Geographical regions also showed that seaside area had the highest percentage of pterygium (seaside area OR = 1.65, 95% CI: 1.35-2.03, and mountainous area OR = 0.58, 95% CI: 0.35-0.95 compared with plain areas). Primary outdoor workers and residents with smoking history had relative higher risk for pterygium (OR = 1.47, 95% CI: 1.17-1.86; OR = 1.36, 95% CI: 1.02-1.83).ConclusionsThe percentage of pterygium in southern Taiwan is about 25.2% among adults aged over 40 years in this survey. It is significantly higher in the age of 50 or more and in residents living in villages along the seaside than those living in the mountainous and the plain areas

Differential Expression and Functional Analysis of the Tristetraprolin Family during Early Differentiation of 3T3-L1 Preadipocytes

The tristetraprolin (TTP) family comprises zinc finger-containing AU-rich element (ARE)-binding proteins consisting of three major members: TTP, ZFP36L1, and ZFP36L2. The present study generated specific antibodies against each TTP member to evaluate its expression during differentiation of 3T3-L1 preadipocytes. In contrast to the inducible expression of TTP, results indicated constitutive expression of ZFP36L1 and ZFP36L2 in 3T3-L1 preadipocytes and their phosphorylation in response to differentiation signals. Physical RNA pull-down and functional luciferase assays revealed that ZFP36L1 and ZFP36L2 bound to the 3′ untranslated region (UTR) of MAPK phosphatase-1 (MKP-1) mRNA and downregulated Mkp-1 3′UTR-mediated luciferase activity. Mkp-1 is an immediate early gene for which the mRNA is transiently expressed in response to differentiation signals. The half-life of Mkp-1 mRNA was longer at 30 min of induction than at 1 h and 2 h of induction. Knockdown of TTP or ZFP36L2 increased the Mkp-1 mRNA half-life at 1 h of induction. Knockdown of ZFP36L1, but not ZFP36L2, increased Mkp-1 mRNA basal levels via mRNA stabilization and downregulated ERK activation. Differentiation induced phosphorylation of ZFP36L1 through ERK and AKT signals. Phosphorylated ZFP36L1 then interacted with 14-3-3, which might decrease its mRNA destabilizing activity. Inhibition of adipogenesis also occurred in ZFP36L1 and TTP knockdown cells. The findings indicate that the differential expression of TTP family members regulates immediate early gene expression and modulates adipogenesis

System Verification and Runtime Monitoring with Multiple Weakly-Hard Constraints

A weakly-hard fault model can be captured by an (m,k) constraint, where 0≤ m ≤ k , meaning that there are at most m bad events (faults) among any k consecutive events. In this article, we use a weakly-hard fault model to constrain the occurrences of faults in system inputs. We develop approaches to verify properties for all possible values of (m,k) , where k is smaller than or equal to a given  K , in an exact and efficient manner. By verifying all possible values of (m,k) , we define weakly-hard requirements for the system environment and design a runtime monitor based on counting the number of faults in system inputs. If the system environment satisfies the weakly-hard requirements, then the satisfaction of desired properties is guaranteed; otherwise, the runtime monitor can notify the system to switch to a safe mode. This is especially essential for cyber-physical systems that need to provide guarantees with limited resources and the existence of faults. Experimental results with discrete second-order control, network routing, vehicle following, and lane changing demonstrate the generality and the efficiency of the proposed approaches. </jats:p

An Asynchronous Multi-Sensor Micro Control Unit for Wireless Body Sensor Networks (WBSNs)

In this work, an asynchronous multi-sensor micro control unit (MCU) core is proposed for wireless body sensor networks (WBSNs). It consists of asynchronous interfaces, a power management unit, a multi-sensor controller, a data encoder (DE), and an error correct coder (ECC). To improve the system performance and expansion abilities, the asynchronous interface is created for handshaking different clock domains between ADC and RF with MCU. To increase the use time of the WBSN system, a power management technique is developed for reducing power consumption. In addition, the multi-sensor controller is designed for detecting various biomedical signals. To prevent loss error from wireless transmission, use of an error correct coding technique is important in biomedical applications. The data encoder is added for lossless compression of various biomedical signals with a compression ratio of almost three. This design is successfully tested on a FPGA board. The VLSI architecture of this work contains 2.68-K gate counts and consumes power 496-μW at 133-MHz processing rate by using TSMC 0.13-μm CMOS process. Compared with the previous techniques, this work offers higher performance, more functions, and lower hardware cost than other micro controller designs

Advanced Ionospheric Probe scientific mission onboard FORMOSAT-5 satellite

Advanced Ionospheric Probe (AIP) is a piggyback science payload developed by National Central University for FORMOSAT-5 satellite to explore space weather/climate and seismic precursors associated with strong earthquakes. The AIP is an all-in-one plasma sensor that measures ionospheric plasma concentrations, velocities, and temperatures in a time-sharing way and is capable of measuring ionospheric plasma irregularities at a sample rate up to 8192 Hz over a wide range of spatial scales. Electroformed gold grids used in the AIP in theory construct planar electric potential surfaces better than woven grids. Moreover, a plasma injection test performed in the Space Plasma Simulation Chamber has verified that no significant hysteresis is found in current-voltage curves measured by the AIP. It indicates that the AIP can make an accurate measurement of the ionospheric plasma parameters in space. Finally, Ionospheric Plasma and Electrodynamics Instrument (IPEI) observations onboard the ROCSAT-1 satellite are applied to show that the scientific objectives of ionospheric space weather/climate and seismo-ionospheric precursors (SIPs) of the FORMOSAT-5/AIP can be fulfilled. The observations reveal that ion parameter global distributions are helpful in studying the formation and variation in temperature crests and troughs in the 2200 - 2300 local time sector, as well as SIPs in the density and the velocity over the epicenter area, which are anticipated for the FORMOSAT-5 satellite orbit