The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. Howev...
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The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.
Chamuangone, a natural compound extracted from Garcinia cowa leaves, has demonstrated potential in cancer therapeutics, but its effects on lung cancer cells remain unclear. This study investigates the apoptotic effect...
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International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information for the public. However, these kinds of information available from HapMap and HGDP are...
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International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information for the public. However, these kinds of information available from HapMap and HGDP are limited mainly due to the small size of samples in both databases. Recently we conducted genome-wide association study (GWAS) with 8,842 Korean subjects (Cho et al., Nature Genetics 2009). In an effort to build a publicly available browsing system for genome data resulted from our large scale GWAS, we developed the browser, namely Korea Association REsource (KARE) browser. This browser provides users with a large scale of single nucleotide polymorphisms (SNP) information comprising 1.5 million SNPs from population-based cohorts of 8,842 samples. KAREBrowser was based on the generic genome browser (GBrowse) that is a web-based application tool developed for users to navigate and visualize the genomic features and annotations in an interactive manner. All SNP information and related functions are available at the web site http://***/karebrowser/.
Recent advancement of high-throughput genotyping technologies has enabled us to carry out a genome-wide association study (GWAS) in a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNP) ...
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Recent advancement of high-throughput genotyping technologies has enabled us to carry out a genome-wide association study (GWAS) in a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNP) is still a troublesome task for researchers to encounter in conducting GWAS. Several difficulties in using analysis tools are one of the major challenges for researchers such as compatibility and dependencies during installation process of softwares. This is a huge obstacle to research institute without computing facilities and specialists. Thus proper research environment is an urgent demand for researchers working on GWAS. We developed BioSMACK to provide research environment for GWAS with no configuration and easy usage. BioSMACK is based on Ubuntu Live CD that offers complete linux-based operating system environment without installation. Moreover, we provide users with GWAS manual that is consist of series of guidelines for GWAS and useful examples. BioSMACK is freely available at http://***/biosmack.
Multifactor dimensionality reduction (MDR) method has been widely applied to detect gene-gene interactions that are well recognized as playing an important role in understanding complex traits, such as disease suscept...
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Multifactor dimensionality reduction (MDR) method has been widely applied to detect gene-gene interactions that are well recognized as playing an important role in understanding complex traits, such as disease susceptibility. However, because of an exhaustive analysis of MDR, the current MDR software has some limitations to be extended to the genome-wide association studies (GWAS) with a large number of genetic markers up to ~1 million. To overcome this computational problem, we developed CUDA based genome-wide association MDR (cuGWAM) software using efficient hardware accelerators. Not only cuGWAM has better performance than CPU-based MDR methods (original MDR and parallel MDR) and GPU-based other methods (MDRGPU), but also initial construction cost is also less expensive. Furthermore, cuGWAM provides various performance measures to evaluate MDR classifiers, including tau-b, likelihood ratio, normalized mutual information as well as balanced accuracy. Also, cuGWAM provided three methods for handling missing genotypes: complete, available and missing category. Executable cuGWAM are freely available at http://***/cugwam for system with CUDA-enabled GPU devices.
Recent genome-wide association studies on several complex diseases have focused on individual single-nucleotide polymorphism (SNP) analysis; however, not many studies have reported interactions among genes perhaps bec...
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Recent genome-wide association studies on several complex diseases have focused on individual single-nucleotide polymorphism (SNP) analysis; however, not many studies have reported interactions among genes perhaps because the gene-gene and gene-environment interaction analysis could be infeasible due to heavy computing requirements. In this study we propose a new strategy for exploring the interactions among haplotypes. The proposed method consists of two steps. Step 1 tests the single-SNP association of whole genome with multiple testing corrections and finds the haplotype blocks of the significant SNPs. Step 2 performs interaction analysis of haplotypes within blocks. Our proposed method is applied to the rheumatoid arthritis data for Genetic Analysis Workshop 16.
Typical personal medical data contains sensitive information about individuals. Storing or sharing the personal medical data is thus often risky. For example, a short DNA sequence can provide information that can not ...
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Feline infectious peritonitis (FIP) is a lethal, viral-induced immune-mediated disease that remains a challenge for diagnosis and treatment in cats. Proteomic profiling, which analyzes the protein content of biologica...
Feline infectious peritonitis (FIP) is a lethal, viral-induced immune-mediated disease that remains a challenge for diagnosis and treatment in cats. Proteomic profiling, which analyzes the protein content of biological samples, offers the potential to identify novel biomarkers that could improve the diagnosis and management of FIP. This study aims to assess the serum proteome and identify proteins that differentiate healthy cats from cats diagnosed with effusive FIP using liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). A total of 30 cats diagnosed with effusive FIP and 27 clinically normal cats were enrolled. Twenty-three proteins were significantly (p< 0.01, ≥ fivefold change in abundance) differentially expressed between cats with effusive FIP and controls. Among these, the P2X purinoceptor, DNA topoisomerase, Notch receptor 2, and cadherin-17 were identified as key proteins of interest in cats with effusive FIP. Our findings suggest that these differentially expressed proteins could serve as potential diagnostic biomarkers and therapeutic targets for FIP. However, further studies are needed to validate these findings and explore their potential applications.
Bone destruction induced by breast cancer metastasis causes severe complications,including death,in breast cancer *** between cancer cells and skeletal cells in metastatic bone microenvironments is a principal element...
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Bone destruction induced by breast cancer metastasis causes severe complications,including death,in breast cancer *** between cancer cells and skeletal cells in metastatic bone microenvironments is a principal element that drives tumor progression and ***-derived factors play fundamental roles in this form of *** identify soluble factors released from cancer cells in bone metastasis,we established a highly bone-metastatic subline of MDA-MB-231 breast cancer *** subline(mtMDA)showed a markedly elevated ability to secrete S100A4 protein,which directly stimulated osteoclast formation via surface receptor *** S100A4 stimulated osteoclastogenesis in vitro and bone loss in *** medium from mtMDA cells in which S100A4 was knocked down had a reduced ability to stimulate ***,the S100A4 knockdown cells elicited less bone destruction in mice than the control knockdown *** addition,administration of an anti-S100A4 monoclonal antibody(mAb)that we developed attenuated the stimulation of osteoclastogenesis and bone loss by mtMDA in *** together,our results suggest that S100A4 released from breast cancer cells is an important player in the osteolysis caused by breast cancer bone metastasis.
Breast cancer is classified into five intrinsic subtypes, with differing treatment methods and prognoses. Therefore, accurate identification of subtypes from patient transcriptome data is essential. Many gene signatur...
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