27 research outputs found
Statistical Methods For Detecting Genetic Risk Factors of a Disease with Applications to Genome-Wide Association Studies
Get PDFThis thesis aims to develop various statistical methods for analysing the data derived from genome wide association studies (GWAS).
The GWAS often involves genotyping individual human genetic variation, using high-throughput genome-wide single nucleotide polymorphism (SNP) arrays, in thousands of individuals and testing for association between those variants and a given disease under the assumption of common disease/common variant.
Although GWAS have identified many potential genetic factors in the genome that affect the risks to complex
diseases, there is still much of the genetic heritability that remains unexplained. The power of
detecting new genetic risk variants can be improved by considering multiple genetic variants simultaneously with novel statistical methods.
Improving the analysis of the GWAS data has received much attention from statisticians and other scientific researchers over the past decade.
There are several challenges arising in analysing the GWAS data. First, determining the risk SNPs might be difficult due to non-random correlation between SNPs that can inflate type I and II errors in statistical inference. When a group of SNPs are considered together in the context of haplotypes/genotypes, the distribution of the haplotypes/genotypes is sparse, which makes it difficult to detect risk haplotypes/genotypes in terms of disease penetrance.
In this work, we proposed four new methods to identify risk haplotypes/genotypes based on their frequency differences between cases and controls. To evaluate the performances of our methods, we simulated datasets under wide range of scenarios according to both retrospective and prospective designs.
In the first method, we first reconstruct haplotypes by using unphased genotypes, followed by clustering and thresholding the inferred haplotypes into risk and non-risk groups with a two-component binomial-mixture model. In the method, the parameters were estimated by using the modified Expectation-Maximization algorithm, where the maximisation step was replaced the posterior sampling of the component parameters. We also elucidated the relationships between risk and non-risk haplotypes under different modes of inheritance and genotypic relative risk.
In the second method, we fitted a three-component mixture model to genotype data directly, followed by an odds-ratio thresholding.
In the third method, we combined the existing haplotype reconstruction software PHASE and permutation method to infer risk haplotypes.
In the fourth method, we proposed a new way to score the genotypes by clustering and combined it with a logistic regression approach to infer risk haplotypes.
The simulation studies showed that the first three methods outperformed the multiple testing method of (Zhu, 2010) in terms of average specificity and sensitivity (AVSS) in all scenarios considered. The logistic regression methods also outperformed the standard logistic regression method.
We applied our methods to two GWAS datasets on coronary artery disease (CAD) and hypertension (HT), detecting several new risk haplotypes and recovering a number of the existing disease-associated genetic variants in the literature
Socio-economic factors associated with delivery assisted by traditional birth attendants in Iraq, 2000
Get PDF<p>Abstract</p> <p>Background</p> <p>Traditional birth attendants (TBAs) are likely to deliver lower quality maternity care compared to professional health workers. It is important to characterize women who are assisted by TBAs in order to design interventions specific to such groups. We thus conducted a study to assess if socio-economic status and demographic factors are associated with having childbirth supervised by traditional birth attendants in Iraq.</p> <p>Methods</p> <p>Iraqi Multiple Indicator Cluster Survey (MICS) data for 2000 were used. We estimated frequencies and proportions of having been delivered by a traditional birth attendant and other social characteristics. Logistic regression analysis was used to assess the association between having been delivered by a TBA and wealth, area of residence (urban versus rural), parity, maternal education and age.</p> <p>Results</p> <p>Altogether 22,980 women participated in the survey, and of these women, 2873 had delivery information and whether they were assisted by traditional birth attendants (TBAs) or not during delivery. About 1 in 5 women (26.9%) had been assisted by TBAs. Compared to women of age 35 years or more, women of age 25–34 years were 22% (AOR = 1.22, 95%CI [1.08, 1.39]) more likely to be assisted by TBAs during delivery. Women who had no formal education were 42% (AOR = 1.42, 95%CI [1.22, 1.65]) more likely to be delivered by TBAs compared to those who had attained secondary or higher level of education. Women in the poorest wealth quintile were 2.52 (AOR = 2.52, 95%CI [2.14, 2.98]) more likely to be delivered by TBAs compared to those in the richest quintile. Compared to women who had 7 or more children, those who had 1 or 2 were 28% (AOR = 0.72, 95%CI [0.59, 0.87]) less likely to be delivered by TBAs.</p> <p>Conclusion</p> <p>Findings from this study indicate that having delivery supervised by traditional birth attendants was associated with young maternal age, low education, and being poor. Meanwhile women having 1 or 2 children were less likely to be delivered by TBAs. These factors should be considered in the design of interventions to reduce the rate of deliveries assisted by TBAs in favour of professional midwives, and consequently reduce maternal and neonatal mortality rates and other adverse events.</p
Iraqi Official Gazette 1993-English
No full textAlwaqai Aliraqiya: The Official Gazette of the Republic of Ira
Iraqi Official Gazette 1986-English
No full textAlwaqai Aliraqiya: The Official Gazette of the Republic of Ira
Iraqi Official Gazette 1990-English
No full textAlwaqai Aliraqiya: The Official Gazette of the Republic of Ira
