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1.  Functional Analysis of Variance for Association Studies 
PLoS ONE  2014;9(9):e105074.
While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods – SKAT and a previously proposed method based on functional linear models (FLM), – especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.
PMCID: PMC4171465  PMID: 25244256
2.  FlexiTerm: a flexible term recognition method 
The increasing amount of textual information in biomedicine requires effective term recognition methods to identify textual representations of domain-specific concepts as the first step toward automating its semantic interpretation. The dictionary look-up approaches may not always be suitable for dynamic domains such as biomedicine or the newly emerging types of media such as patient blogs, the main obstacles being the use of non-standardised terminology and high degree of term variation.
In this paper, we describe FlexiTerm, a method for automatic term recognition from a domain-specific corpus, and evaluate its performance against five manually annotated corpora. FlexiTerm performs term recognition in two steps: linguistic filtering is used to select term candidates followed by calculation of termhood, a frequency-based measure used as evidence to qualify a candidate as a term. In order to improve the quality of termhood calculation, which may be affected by the term variation phenomena, FlexiTerm uses a range of methods to neutralise the main sources of variation in biomedical terms. It manages syntactic variation by processing candidates using a bag-of-words approach. Orthographic and morphological variations are dealt with using stemming in combination with lexical and phonetic similarity measures. The method was evaluated on five biomedical corpora. The highest values for precision (94.56%), recall (71.31%) and F-measure (81.31%) were achieved on a corpus of clinical notes.
FlexiTerm is an open-source software tool for automatic term recognition. It incorporates a simple term variant normalisation method. The method proved to be more robust than the baseline against less formally structured texts, such as those found in patient blogs or medical notes. The software can be downloaded freely at
PMCID: PMC3853334  PMID: 24112363
3.  Using Prior Information from the Medical Literature in GWAS of Oral Cancer Identifies Novel Susceptibility Variant on Chromosome 4 - the AdAPT Method 
PLoS ONE  2012;7(5):e36888.
Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS.
We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer.
Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [ptrend] = 2.5×10−3). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76–0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found.
This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url:
PMCID: PMC3360735  PMID: 22662130
4.  Temperature effect on tert-butyl alcohol (TBA) biodegradation kinetics in hyporheic zone soils 
Remediation of tert-butyl alcohol (TBA) in subsurface waters should be taken into consideration at reformulated gasoline contaminated sites since it is a biodegradation intermediate of methyl tert-butyl ether (MTBE), ethyl tert-butyl ether (ETBE), and tert-butyl formate (TBF). The effect of temperature on TBA biodegradation has not been not been published in the literature.
Biodegradation of [U 14C] TBA was determined using hyporheic zone soil microcosms.
First order mineralization rate constants of TBA at 5°C, 15°C and 25°C were 7.84 ± 0.14 × 10-3, 9.07 ± 0.09 × 10-3, and 15.3 ± 0.3 × 10-3 days-1, respectively (or 2.86 ± 0.05, 3.31 ± 0.03, 5.60 ± 0.14 years-1, respectively). Temperature had a statistically significant effect on the mineralization rates and was modelled using the Arrhenius equation with frequency factor (A) and activation energy (Ea) of 154 day-1 and 23,006 mol/J, respectively.
Results of this study are the first to determine mineralization rates of TBA for different temperatures. The kinetic rates determined in this study can be used in groundwater fate and transport modelling of TBA at the Ronan, MT site and provide an estimate for TBA removal at other similar shallow aquifer sites and hyporheic zones as a function of seasonal change in temperature.
PMCID: PMC2174489  PMID: 17877835

Results 1-4 (4)