1,721,241 research outputs found
Analysis of candidate regions for susceptibility to multiple sclerosis: comparison of a proposed analytical multi-allele haplotype association test and a permutation test
No full textStatistical approaches for copy number variation detection and association with complex human phenotypes
Full text linkCopy number variants (CNVs) play an important role in the disease pathogenesis, including epilepsy, diabetes and many others. CNVs, are also known to affect cellular phenotypes through several phenomenon such as gene dosage.
Next generation technologies for sequencing (DNA and RNA) and metabolite profiling (metabolomics) has led to the systematic discovery and evaluation of various genomic variants and their relationship to multiple phenotypes. Such approaches often involve application of several statistical and machine learning methods for unravelling new relationships between genomic variants and phenotypes i.e. disease outcomes or quantitative traits characterized at the molecular level.
This thesis explores and develops several statistical methods for CNV detection and association with complex human phenotypes, in particular for epilepsy drug-response, epilepsy susceptibility, metabolomics and gene expression.
In more detail, chapter 3, describes a genome wide CNV association analysis for two phenotypes including epilepsy susceptibility and epilepsy drug response. I have identified several important candidate genes for these two phenotypes, including the top most associated genes, SLC9A1 (p-value=6.69E-15) for epilepsy susceptibility and WWOX (p-value=1.93E-3) for epilepsy drug response. These associations were replicated in a separate Australian cohort and were further validated in lab and in-silico, leading to some positive and negative confirmation.
In chapter 4, I present CNV association with metabolomic data in the exonic regions of the TSPAN8 gene. A strong association signal was detected in the 6th exon and 7th exon of the TSPAN8 gene, where a large proportion of metabonomic lipid phenotypes were found to be associated with univariate (P-value=7.64E-4) and multivariate (P-value=1.33E-6) approaches. These CNVs were also found to be nominally associated with type 2 diabetes (P-value=3.32e-7). In addition, I also carried out advanced multivariate based association analysis to corroborate these results and further reported sequencing based validation results for TSPAN8 exonic CNVs in different human populations from the 1000 genomes project.
In chapter 5, I report a genome wide CNV association analysis with gene expression in ten different regions of the human brain. I identified a novel CNV near the DRD5 gene which was found to be strongly associated with gene expression. Further, I have reported on-going efforts to replicate and validate this finding.
Each of these different phenotype categories analysed posed its own unique challenges and required specific approaches for analysis and interpretation.Open Acces
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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