SNPTransformer: A Lightweight Toolkit for Genome-Wide Association Studies

AbstractHigh-throughput genotyping chips have produced huge datasets for genome-wide association studies (GWAS) that have contributed greatly to discovering susceptibility genes for complex diseases. There are two strategies for performing data analysis for GWAS. One strategy is to use open-source or commercial packages that are designed for GWAS. The other is to take advantage of classic genetic programs with specific functions, such as linkage disequilibrium mapping, haplotype inference and transmission disequilibrium tests. However, most classic programs that are available are not suitable for analyzing chip data directly and require custom-made input, which results in the inconvenience of converting raw genotyping files into various data formats. We developed a powerful, user-friendly, lightweight program named SNPTransformer for GWAS that includes five major modules (Transformer, Operator, Previewer, Coder and Simulator). The toolkit not only works for transforming the genotyping files into ten input formats for use with classic genetics packages, but also carries out useful functions such as relational operations on IDs, previewing data files, recoding data formats and simulating marker files, among other functions. It bridges upstream raw genotyping data with downstream genetic programs, and can act as an in-hand toolkit for human geneticists, especially for non-programmers. SNPTransformer is freely available at http://snptransformer.sourceforge.net

Detecting transmission and reassortment events for influenza A viruses with genotype profile method

Evolutionary events of transmission and reassortment for influenza A viruses were traditionally detected by phylogenetic analysis for influenza viruses' eight gene segments. Because the phylogenetic analysis can be complex, we developed genotype profile method which packaged the phylogenetic algorithms to analyze combination patterns of gene segments and integrated epidemiology knowledge. With the method, the analysis of reassortment and transmission becomes a simple and reliable process that combines genotypes, which is identical for the biological process of the virus. An application called IVEE that implements the method is available for all academic users to apply the method http://snptransformer.sourceforge.net. Furthermore, we found that a previous summary of the reassortment events in swine influenza A viruses may be inaccurate

The impact of reliable range estimation on battery electric vehicle feasibility

Range limitation is a significant obstacle to market acceptance of battery electric vehicles (BEVs). Range anxiety is exacerbated when drivers could not reliably predict the remaining battery range or when their journeys were unexpectedly extended. This paper quantifies the impact of reliable range estimation on BEV feasibility using GPS-tracked travel survey data, collected over an 18-month period (from November 2004 to April 2006) in the Seattle metropolitan area. BEV feasibility is quantified as the number of days when travel adaption is needed if a driver replaces a conventional gasoline vehicle (CGV) with a BEV. The distribution of BEV range is estimated based on the real-world fuel efficiency data. A driver is assumed to choose between using a BEV or a substitute gasoline vehicle, based on the cumulative prospect theory (CPT). BEV is considered feasible for a particular driver if he/she needs to use a substitute vehicle on less than 0.5% of the travel days. By varying the values of some CPT parameter, the percentage of BEV feasible vehicles could change from less than 5% to 25%. The numerical results also show that with a 50% reduction in the standard deviation and 50% increase in the mean of the BEV range distribution BEV feasibility increases from less than 5% of the sampled drivers to 30%

Monitoring the Process of Endostar-Induced Tumor Vascular Normalization by Non-contrast Intravoxel Incoherent Motion Diffusion-Weighted MRI

Tumor vascular normalization has been proposed as a new concept in anti-tumor angiogenesis, and the normalization window is considered as an opportunity to increase the effect of chemoradiotherapy. However, there is still a lack of a non-invasive method for monitoring the process of tumor vascular normalization. Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM DW-MRI) is an emerging approach which can effectively assess microperfusion in tumors, without the need for exogenous contrast agents. However, its role in monitoring tumor vascular normalization still needs further study. In this study, we established a tumor vascular normalization model of CT26 colon-carcinoma-bearing mice by means of Endostar treatment. We then employed IVIM DW-MRI and immunofluorescence to detect the process of tumor vascular normalization at different times after treatment. We found that the D* values of the Endostar group were significantly higher than those of the control group on days 4, 6, 8, and 10 after treatment, and the f values of the Endostar group were significantly higher than those of the control group on days 6 and 8. Furthermore, we confirmed through analysis of histologic parameters that Endostar treatment induced the CT26 tumor vascular normalization window starting from day 4 after treatment, and this window lasted for 6 days. Moreover, we found that D* and f values were well correlated with pericyte coverage (r = 0.469 and 0.504, respectively; P < 0.001, both) and relative perfusion (r = 0.424 and 0.457, respectively; P < 0.001, both). Taken together, our findings suggest that IVIM DW-MRI has the potential to serve as a non-invasive approach for monitoring Endostar-induced tumor vascular normalization

Polymorphisms in the ADRB2 gene and Graves disease: a case-control study and a meta-analysis of available evidence

<p>Abstract</p> <p>Background</p> <p>The beta-2-Adrenergic receptor (<it>ADRB2</it>) gene on chromosome 5q33.1 is an important immunoregulatory factor. We and others have previously implicated chromosomal region 5q31-33 for contribution to the genetic susceptibility to Graves disease (GD) in East-Asian populations. Two recent studies showed associations between the single nucleotide polymorphism (SNP) rs1042714 in the <it>ADRB2 </it>gene and GD. In this study, we aimed to fully investigate whether the <it>ADRB2 </it>gene conferred susceptibility to GD in Chinese population, and to perform a meta-analysis of association between <it>ADRB2 </it>and GD.</p> <p>Methods</p> <p>Approximately 1 kb upstream the transcription start site and the entire coding regions of the <it>ADRB2 </it>gene were resequenced in 48 Han Chinese individuals to determine the linkage disequilibrium (LD) patterns. Tag SNPs were selected and genotyped in a case-control collection of 1,118 South Han Chinese subjects, which included 428 GD patients and 690 control subjects. A meta-analysis was performed with the data obtained in the present samples and those available from prior studies.</p> <p>Results</p> <p>Fifteen SNPs in the <it>ADRB2 </it>gene were identified by resequencing and one SNP was novel. Ten tag SNPs were investigated further to assess association of <it>ADRB2 </it>in the case-control collection. Neither individual tag SNP nor haplotypes showed association with GD in Han Chinese population (P > 0.05). Our meta-analysis of the <it>ADRB2 </it>SNP rs1042714 measured heterogeneity between the ethnic groups (I²= 53.1%) and no association to GD was observed in the overall three studies with a random effects model (OR = 1.13, 95% CI, 0.95 to 1.36; P = 0.18). However, significant association was found from the combined data of Caucasian population with a fixed effects model (OR = 1.18, 95% CI, 1.06 to 1.32; P = 0.002; I²= 5.9%).</p> <p>Conclusion</p> <p>Our study indicated that the <it>ADRB2 </it>gene did not exert a substantial influence on GD susceptibility in Han Chinese population, but contributed to a detectable GD risk in Caucasian population. This inconsistency resulted largely from between-ethnicity heterogeneity.</p

Gene-Centric Characteristics of Genome-Wide Association Studies

BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions

Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data

This paper studies electric vehicle charger location problems and analyzes the impact of public charging infrastructure deployment on increasing electric miles traveled, thus promoting battery electric vehicle (BEV) market penetration. An activity-based assessment method is proposed to evaluate BEV feasibility for the heterogeneous traveling population in the real world driving context. Genetic algorithm is applied to find (sub)optimal locations for siting public charging stations. A case study using the GPS-based travel survey data collected in the greater Seattle metropolitan area shows that electric miles and trips could be significantly increased by installing public chargers at popular destinations, with a reasonable infrastructure investment.This is a manuscript of an article published as Dong, Jing, Changzheng Liu, and Zhenhong Lin. "Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data." Transportation Research Part C: Emerging Technologies 38 (2014): 44-55. doi: 10.1016/j.trc.2013.11.001. Posted with permission.</p

A Novel Method of Production Line Bearing Fault Diagnosis Based on 2D Image and Cross-Domain Few-Shot Learning

Data-driven intelligent fault diagnosis has made considerable strides. However, collecting sufficient fault information in real production data is extremely challenging. Therefore, a novel method of bearing fault diagnosis based on two-dimensional (2D) images and cross-domain few-shot learning is proposed. Initially, the approach uses multiscale morphology to convert the bearing’s one-dimensional (1D) vibration signal into a 2D image, which preserves the whole information. Second, to address the issue of limited bearing fault data, we extend a substantial amount of natural image knowledge to the converted 2D image based on the improved cross-domain few-shot learning method. A distance-based classifier is employed to prevent the problem of overfitting owing to insufficient data to improve the approach’s classification capacity with few samples. The experimental results demonstrate that, with the limited dataset provided, our method outperforms other prevalent methods and has high feasibility and certain engineering applications

A Fast and On-Machine Measuring System Using the Laser Displacement Sensor for the Contour Parameters of the Drill Pipe Thread

The inconvenient loading and unloading of a long and heavy drill pipe gives rise to the difficulty in measuring the contour parameters of its threads at both ends. To solve this problem, in this paper we take the SCK230 drill pipe thread-repairing machine tool as a carrier to design and achieve a fast and on-machine measuring system based on a laser probe. This system drives a laser displacement sensor to acquire the contour data of a certain axial section of the thread by using the servo function of a CNC machine tool. To correct the sensor’s measurement errors caused by the measuring point inclination angle, an inclination error model is built to compensate data in real time. To better suppress random error interference and ensure real contour information, a new wavelet threshold function is proposed to process data through the wavelet threshold denoising. Discrete data after denoising is segmented according to the geometrical characteristics of the drill pipe thread, and the regression model of the contour data in each section is fitted by using the method of weighted total least squares (WTLS). Then, the thread parameters are calculated in real time to judge the processing quality. Inclination error experiments show that the proposed compensation model is accurate and effective, and it can improve the data acquisition accuracy of a sensor. Simulation results indicate that the improved threshold function is of better continuity and self-adaptability, which makes sure that denoising effects are guaranteed, and, meanwhile, the complete elimination of real data distorted in random errors is avoided. Additionally, NC50 thread-testing experiments show that the proposed on-machine measuring system can complete the measurement of a 25 mm thread in 7.8 s, with a measurement accuracy of ±8 μm and repeatability limit ≤ 4 μm (high repeatability), and hence the accuracy and efficiency of measurement are both improved