Analysis of association studies and inference of haplotypic phase using hidden Markov models

In this thesis I focus on the development and application of hidden Markov model (HMM) to solve problems in statistical genetics. Our method, based on a HMM, models the joint haplotype structure in the samples, where the parameters in the model are estimated by the Baum-Welch EM algorithm. Also, the model does not require pre-defined blocks or a sliding window scheme to define haplotype boundaries. Thus our method is computationally efficient and applicable for either the whole genome sequence or the candidate gene sequence. The first application of this model is for disease association testing using inferred ancestral haplotypes. We employed a HMM to cluster haplotypes into groups of predicted common ancestral haplotypes from diploid genotypes. The results from simulation studies show that our method greatly outperforms single-SNP analyses and has greater power than a haplotype-based method, CLADHC, in most simulation scenarios. The second application is for inferring haplotypic phase and to predict missing genotypes in polyploid organisms. Using a simulation study we demonstrate that the method provides accurate estimates of haplotypic phase and missing genotypes for diploids, triploids and tetraploids. The third application is for joint CNV/SNP haplotype and missing data inference. The results are very encouraging for this application. With the increasing availability of genotype data in both diploid and polyploid organisms, we believe that our programs can facilitate the investigation of genetic variations in genome-wide scale studies

Gapless topological Fulde-Ferrell superfluidity in spin-orbit coupled Fermi gases

Topological superfluids usually refer to a superfluid state which is gapped in the bulk but metallic at the boundary. Here we report that a gapless, topologically non-trivial superfluid with inhomogeneous Fulde-Ferrell pairing order parameter can emerge in a two-dimensional spin-orbit coupled Fermi gas, in the presence of both in-plane and out-of-plane Zeeman fields. The Fulde-Ferrell pairing - induced by the spin-orbit coupling and in-plane Zeeman field - is responsible for this gapless feature. This exotic superfluid has a significant Berezinskii-Kosterlitz-Thouless (BKT) transition temperature and has robust Majorana edge modes against disorder owing to its topological nature.Comment: 5 pages, 5 figures; add the results on the critical BKT temperature and superfluid density, as well as the discussion on the robustness of the chiral edge states against disorde

Inference of haplotypic phase and missing genotypes in polyploid organisms and variable copy number genomic regions

Background: The power of haplotype-based methods for association studies, identification of regions under selection, and ancestral inference, is well-established for diploid organisms. For polyploids, however, the difficulty of determining phase has limited such approaches. Polyploidy is common in plants and is also observed in animals. Partial polyploidy is sometimes observed in humans (e.g. trisomy 21; Down's syndrome), and it arises more frequently in some human tissues. Local changes in ploidy, known as copy number variations (CNV), arise throughout the genome. Here we present a method, implemented in the software polyHap, for the inference of haplotype phase and missing observations from polyploid genotypes. PolyHap allows each individual to have a different ploidy, but ploidy cannot vary over the genomic region analysed. It employs a hidden Markov model (HMM) and a sampling algorithm to infer haplotypes jointly in multiple individuals and to obtain a measure of uncertainty in its inferences. Results: In the simulation study, we combine real haplotype data to create artificial diploid, triploid, and tetraploid genotypes, and use these to demonstrate that polyHap performs well, in terms of both switch error rate in recovering phase and imputation error rate for missing genotypes. To our knowledge, there is no comparable software for phasing a large, densely genotyped region of chromosome from triploids and tetraploids, while for diploids we found polyHap to be more accurate than fastPhase. We also compare the results of polyHap to SATlotyper on an experimentally haplotyped tetraploid dataset of 12 SNPs, and show that polyHap is more accurate. Conclusion: With the availability of large SNP data in polyploids and CNV regions, we believe that polyHap, our proposed method for inferring haplotypic phase from genotype data, will be useful in enabling researchers analysing such data to exploit the power of haplotype-based analyses

Rapid identification of allergenic and pathogenic molds in environmental air by an oligonucleotide array

<p>Abstract</p> <p>Background</p> <p>Airborne fungi play an important role in causing allergy and infections in susceptible people. Identification of these fungi, based on morphological characteristics, is time-consuming, expertise-demanding, and could be inaccurate.</p> <p>Methods</p> <p>We developed an oligonucleotide array that could accurately identify 21 important airborne fungi (13 genera) that may cause adverse health problems. The method consisted of PCR amplification of the internal transcribed spacer (ITS) regions, hybridization of the PCR products to a panel of oligonucleotide probes immobilized on a nylon membrane, and detection of the hybridization signals with alkaline phosphatase-conjugated antibodies.</p> <p>Results</p> <p>A collection of 72 target and 66 nontarget reference strains were analyzed by the array. Both the sensitivity and specificity of the array were 100%, and the detection limit was 10 pg of genomic DNA per assay. Furthermore, 70 fungal isolates recovered from air samples were identified by the array and the identification results were confirmed by sequencing of the ITS and D1/D2 domain of the large-subunit RNA gene. The sensitivity and specificity of the array for identification of the air isolates was 100% (26/26) and 97.7% (43/44), respectively.</p> <p>Conclusions</p> <p>Identification of airborne fungi by the array was cheap and accurate. The current array may contribute to decipher the relationship between airborne fungi and adverse health effect.</p

Toward better intelligent learning (iLearning) performance:what makes iLearning work for students in a university setting?

We explored the critical factors associated with iLearning that impact students’ learning performance and identified the factors with a notable influence to help managers in higher education institutions increase the effectiveness of iLearning for students. We initially synthesised 4 main dimensions (including 26 criteria): performance expectancy, lecturers’ influence, quality of service, and personal innovativeness. Subsequently, we conducted surveys in two stages. First, by studying a group of students with experience using iLearning at Taiwanese universities, we extracted 5 critical dimensions (including 18 criteria) through a factor analysis. Second, by studying a group of senior educators and practitioners in Taiwan, we prioritised the dimensions and criteria through the analytic hierarchy process (AHP). We found that performance expectancy is the top critical dimension, and the top five critical criteria pertain to enhancing the learning performance, increasing the learning participation, altering learning habits, ensuring access at all times, and enabling prompt use of learning resources. Moreover, we recommend several suggestions for the relevant managers to enhance the students’ iLearning performance

Haplotype and isoform specific expression estimation using multi-mapping RNA-seq reads

We present a novel pipeline and methodology for simultaneously estimating isoform expression and allelic imbalance in diploid organisms using RNA-seq data. We achieve this by modeling the expression of haplotype-specific isoforms. If unknown, the two parental isoform sequences can be individually reconstructed. A new statistical method, MMSEQ, deconvolves the mapping of reads to multiple transcripts (isoforms or haplotype-specific isoforms). Our software can take into account non-uniform read generation and works with paired-end reads