Can statistics save the day?

Statistics is usually perceived as dry, boring and not very useful in everyday life. In this public lecture, Dr Nicolas Greliche will try to show you that this is far from true. Following the strange day of a fictitious JCU student, you will see how Statistics can be used in a fun and interesting way to rescue this student from several uncomfortable situations. Chances are (p<0.001) that at the end you will be convinced that Statistics could well at one time or another also save your day

Convincing students that their groupmates' success can increase, not diminish, their own success

Both theory and research support the use of group activities to aid student learning. However, some students are reluctant to learn with peers for fear that the peers will gain more. The article attempts to address this fear. This article provides educators with explanations to give their students as to why, even in norm referenced assessment environments, by helping their groupmates, students are positively, not negatively, impacting their own success on assessments. The article opens with a review of assessment options: norm referenced, criterion referenced and ipsative. Next, Social Interdependence Theory is explained for the insights it might offer as to how students view their peers' success. The article's third section summarises some of the research on peer learning, in particular research on what forms of peer interaction might best promote learning. Finally, the article examines three contexts in which norm referencing is applied - standardised exams, class grades and class ranking – and concludes that the chances are small of groupmates' success diminishing the success of students who have helped their groupmates. This conclusion is reached based, first, on mathematical calculations and, most importantly, on the research based premise that when students provide elaborated help to groupmates, the helpers are likely to boost their own scores

Stratégies de recherches de phénomènes d'interactions dans les maladies multifactorielles

Les études d'associations en génome entier ("GWAS") ont récemment permis la découverte de nombreux polymorphismes génétiques impliqués dans la susceptibilité aux maladies multifactorielles. Cependant, ces polymorphismes n'expliquent qu'une faible part de l'héritabilité génétique de ces maladies, nous poussant ainsi à explorer de nouvelles pistes de recherche. Une des hypothèses envisagées serait qu'une partie de cette héritabilité manquante fasse intervenir des phénomènes d'interactions entre polymorphismes génétiques. L'objectif de cette thèse est d'explorer cette hypothèse en adoptant une stratégie de recherche d'interactions basée sur des critères statistiques et biologiques à partir de données issues de différentes études "GWAS". Ainsi, en utilisant différentes méthodes statistiques, nous avons commencé par rechercher des interactions entre polymorphismes qui pourraient influencer le risque de thrombose veineuse. Cette recherche n'a malheureusement pas abouti à l'identification de résultats robustes vis à vis du problème des tests multiples. Dans un deuxième temps, à partir d'hypothèses "plus biologiques", nous avons tenté de mettre en évidence des interactions entre polymorphismes impliqués dans les mécanismes de régulation de l'expression génique associés aux microARNs. Nous avons pu ainsi montrer de manière robuste dans deux populations indépendantes qu'un polymorphisme au sein de la séquence du microARN hsa-mir-219-1 interagissait avec un polymorphisme du gène HLA-DPB1 pour en moduler l'expression monocytaire. Nous avons également montré que l'expression monocytaire du gène H1F0 était influencée par un phénomène d'interaction impliquant un polymorphisme du microARN hsa-mir-659. En apportant sa propre contribution à l'engouement récent que suscite la recherche d'interactions entre polymorphismes dans les maladies dites complexes, ce travail de thèse illustre clairement la difficulté d'une telle tâche et l'importance de réfléchir à de nouvelles stratégies de recherches.Recently, Genome-Wide Association Studies (GWAS) have led to the discovery of numerous genetic polymorphisms involved in complex human diseases. However, these polymorphisms contribute only a little to the overall genetic variability of these diseases, suggesting the need for new kind of investigations in order to disentangle the so-called "missing heritability". The purpose of my PhD project was to investigate how different research strategies relying on statistical and biological considerations could help in determining whether part of this missing heritability could reside in interaction phenomena between genetic polymorphisms. Firstly, we applied different statistical methodologies and looked for interactions between polymorphisms that could influence the risk of venous thrombosis (VT). Even though this study was based on two large GWAS datasets, we were not able to identify pairwise interactions that survive multiple testing. This work suggests that strong interactive phenomena between common SNPs are unlikely to contribute much to the risk of VT. Second, by adopting a hypothesis-driven approach relying on biological arguments, we sought for interactions between microRNA related polymorphisms that could alter genetic expression. Using two large GWAS datasets in which genome-wide monocyte expression was also available, we were able to demonstrate the existence of two pairwise interaction phenomena on monocyte expression involving miRNAs polymorphisms: 1/ the expression of HLA-DPB1 was modulated by a polymorphism in its 3'UTR region with a polymorphism in the hsa-mir-219-1 microRNA sequence; 2/ similarly, the expression of H1F0 was influenced by a polymorphism in its 3'UTR region interacting with a polymorphism in the microRNA hsa-mir-659. Altogether, this project supports for the role of gene x gene interactions in the interindividual variability of biological processes but their identifications remain a tedious task requiring large samples and the development of new research strategies and methodologies.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Comprehensive exploration of the effects of miRNA SNPs on monocyte gene expression

We aimed to assess whether pri-miRNA SNPs (miSNPs) could influence monocyte gene expression, either through marginal association or by interacting with polymorphisms located in 3'UTR regions (3utrSNPs). We then conducted a genome-wide search for marginal miSNPs effects and pairwise miSNPs × 3utrSNPs interactions in a sample of 1,467 individuals for which genome-wide monocyte expression and genotype data were available. Statistical associations that survived multiple testing correction were tested for replication in an independent sample of 758 individuals with both monocyte gene expression and genotype data. In both studies, the hsa-mir-1279 rs1463335 was found to modulate in cis the expression of LYZ and in trans the expression of CNTN6, CTRC, COPZ2, KRT9, LRRFIP1, NOD1, PCDHA6, ST5 and TRAF3IP2 genes, supporting the role of hsa-mir-1279 as a regulator of several genes in monocytes. In addition, we identified two robust miSNPs × 3utrSNPs interactions, one involving HLA-DPB1 rs1042448 and hsa-mir-219-1 rs107822, the second the H1F0 rs1894644 and hsa-mir-659 rs5750504, modulating the expression of the associated genes. As some of the aforementioned genes have previously been reported to reside at disease-associated loci, our findings provide novel arguments supporting the hypothesis that the genetic variability of miRNAs could also contribute to the susceptibility to human diseases

Genetics of venous thrombosis: insights from a new genome wide association study

Background: Venous Thrombosis (VT) is a common multifactorial disease associated with a major public health burden. Genetics factors are known to contribute to the susceptibility of the disease but how many genes are involved and their contribution to VT risk still remain obscure. We aimed to identify genetic variants associated with VT risk. Methodology/Principal Findings: We conducted a genome-wide association study (GWAS) based on 551,141 SNPs genotyped in 1,542 cases and 1,110 controls. Twelve SNPs reached the genome-wide significance level of 2.0×10−8 and encompassed four known VT-associated loci, ABO, F5, F11 and FGG. By means of haplotype analyses, we also provided novel arguments in favor of a role of HIVEP1, PROCR and STAB2, three loci recently hypothesized to participate in the susceptibility to VT. However, no novel VT-associated loci came out of our GWAS. Using a recently proposed statistical methodology, we also showed that common variants could explain about 35% of the genetic variance underlying VT susceptibility among which 3% could be attributable to the main identified VT loci. This analysis additionally suggested that the common variants left to be identified are not uniformly distributed across the genome and that chromosome 20, itself, could contribute to ∼7% of the total genetic variance. Conclusions/Significance: This study might also provide a valuable source of information to expand our understanding of biological mechanisms regulating quantitative biomarkers for VT

Stat321, an on-line statistics textbook based on intuitive inferential reasoning

Research in human cognition has shown that people possess intuitive notions of statistics, but may fail to generate correct judgments in a number of situations. These characteristics of the human mind can be used to introduce statistical concepts and warn against misconceptions by showing parallels and divergences between proper statistical thinking and intuition. To date, this approach has been little investigated resulting in a lack of resources for the interested teacher. Here, I present Stat321, a project of an atypical online statistics textbook which uses the naive statistical thinking of the reader to explain the what, why and how of Statistics. Stat321 is designed to evolve with comments, ideas and the advances in statistics education research. Initial feedback from undergraduate students is discussed

Stratégies de recherches de phénomènes d’interactions dans les maladies multifactorielles

Recently, Genome-Wide Association Studies (GWAS) have led to the discovery of numerous genetic polymorphisms involved in complex human diseases. However, these polymorphisms contribute only a little to the overall genetic variability of these diseases, suggesting the need for new kind of investigations in order to disentangle the so-called "missing heritability". The purpose of my PhD project was to investigate how different research strategies relying on statistical and biological considerations could help in determining whether part of this missing heritability could reside in interaction phenomena between genetic polymorphisms. Firstly, we applied different statistical methodologies and looked for interactions between polymorphisms that could influence the risk of venous thrombosis (VT). Even though this study was based on two large GWAS datasets, we were not able to identify pairwise interactions that survive multiple testing. This work suggests that strong interactive phenomena between common SNPs are unlikely to contribute much to the risk of VT. Second, by adopting a hypothesis-driven approach relying on biological arguments, we sought for interactions between microRNA related polymorphisms that could alter genetic expression. Using two large GWAS datasets in which genome-wide monocyte expression was also available, we were able to demonstrate the existence of two pairwise interaction phenomena on monocyte expression involving miRNAs polymorphisms: 1/ the expression of HLA-DPB1 was modulated by a polymorphism in its 3'UTR region with a polymorphism in the hsa-mir-219-1 microRNA sequence; 2/ similarly, the expression of H1F0 was influenced by a polymorphism in its 3'UTR region interacting with a polymorphism in the microRNA hsa-mir-659. Altogether, this project supports for the role of gene x gene interactions in the interindividual variability of biological processes but their identifications remain a tedious task requiring large samples and the development of new research strategies and methodologies.Les études d'associations en génome entier ("GWAS") ont récemment permis la découverte de nombreux polymorphismes génétiques impliqués dans la susceptibilité aux maladies multifactorielles. Cependant, ces polymorphismes n'expliquent qu'une faible part de l'héritabilité génétique de ces maladies, nous poussant ainsi à explorer de nouvelles pistes de recherche. Une des hypothèses envisagées serait qu'une partie de cette héritabilité manquante fasse intervenir des phénomènes d'interactions entre polymorphismes génétiques. L'objectif de cette thèse est d'explorer cette hypothèse en adoptant une stratégie de recherche d'interactions basée sur des critères statistiques et biologiques à partir de données issues de différentes études "GWAS". Ainsi, en utilisant différentes méthodes statistiques, nous avons commencé par rechercher des interactions entre polymorphismes qui pourraient influencer le risque de thrombose veineuse. Cette recherche n'a malheureusement pas abouti à l'identification de résultats robustes vis à vis du problème des tests multiples. Dans un deuxième temps, à partir d'hypothèses "plus biologiques", nous avons tenté de mettre en évidence des interactions entre polymorphismes impliqués dans les mécanismes de régulation de l'expression génique associés aux microARNs. Nous avons pu ainsi montrer de manière robuste dans deux populations indépendantes qu'un polymorphisme au sein de la séquence du microARN hsa-mir-219-1 interagissait avec un polymorphisme du gène HLA-DPB1 pour en moduler l'expression monocytaire. Nous avons également montré que l'expression monocytaire du gène H1F0 était influencée par un phénomène d'interaction impliquant un polymorphisme du microARN hsa-mir-659. En apportant sa propre contribution à l'engouement récent que suscite la recherche d'interactions entre polymorphismes dans les maladies dites complexes, ce travail de thèse illustre clairement la difficulté d'une telle tâche et l'importance de réfléchir à de nouvelles stratégies de recherches

Research strategies for finding genetic interaction phenomena in multifactorial diseases

Les études d'associations en génome entier ("GWAS") ont récemment permis la découverte de nombreux polymorphismes génétiques impliqués dans la susceptibilité aux maladies multifactorielles. Cependant, ces polymorphismes n'expliquent qu'une faible part de l'héritabilité génétique de ces maladies, nous poussant ainsi à explorer de nouvelles pistes de recherche. Une des hypothèses envisagées serait qu'une partie de cette héritabilité manquante fasse intervenir des phénomènes d'interactions entre polymorphismes génétiques. L'objectif de cette thèse est d'explorer cette hypothèse en adoptant une stratégie de recherche d'interactions basée sur des critères statistiques et biologiques à partir de données issues de différentes études "GWAS". Ainsi, en utilisant différentes méthodes statistiques, nous avons commencé par rechercher des interactions entre polymorphismes qui pourraient influencer le risque de thrombose veineuse. Cette recherche n'a malheureusement pas abouti à l'identification de résultats robustes vis à vis du problème des tests multiples. Dans un deuxième temps, à partir d'hypothèses "plus biologiques", nous avons tenté de mettre en évidence des interactions entre polymorphismes impliqués dans les mécanismes de régulation de l'expression génique associés aux microARNs. Nous avons pu ainsi montrer de manière robuste dans deux populations indépendantes qu'un polymorphisme au sein de la séquence du microARN hsa-mir-219-1 interagissait avec un polymorphisme du gène HLA-DPB1 pour en moduler l'expression monocytaire. Nous avons également montré que l'expression monocytaire du gène H1F0 était influencée par un phénomène d'interaction impliquant un polymorphisme du microARN hsa-mir-659. En apportant sa propre contribution à l'engouement récent que suscite la recherche d'interactions entre polymorphismes dans les maladies dites complexes, ce travail de thèse illustre clairement la difficulté d'une telle tâche et l'importance de réfléchir à de nouvelles stratégies de recherches.Recently, Genome-Wide Association Studies (GWAS) have led to the discovery of numerous genetic polymorphisms involved in complex human diseases. However, these polymorphisms contribute only a little to the overall genetic variability of these diseases, suggesting the need for new kind of investigations in order to disentangle the so-called "missing heritability". The purpose of my PhD project was to investigate how different research strategies relying on statistical and biological considerations could help in determining whether part of this missing heritability could reside in interaction phenomena between genetic polymorphisms. Firstly, we applied different statistical methodologies and looked for interactions between polymorphisms that could influence the risk of venous thrombosis (VT). Even though this study was based on two large GWAS datasets, we were not able to identify pairwise interactions that survive multiple testing. This work suggests that strong interactive phenomena between common SNPs are unlikely to contribute much to the risk of VT. Second, by adopting a hypothesis-driven approach relying on biological arguments, we sought for interactions between microRNA related polymorphisms that could alter genetic expression. Using two large GWAS datasets in which genome-wide monocyte expression was also available, we were able to demonstrate the existence of two pairwise interaction phenomena on monocyte expression involving miRNAs polymorphisms: 1/ the expression of HLA-DPB1 was modulated by a polymorphism in its 3'UTR region with a polymorphism in the hsa-mir-219-1 microRNA sequence; 2/ similarly, the expression of H1F0 was influenced by a polymorphism in its 3'UTR region interacting with a polymorphism in the microRNA hsa-mir-659. Altogether, this project supports for the role of gene x gene interactions in the interindividual variability of biological processes but their identifications remain a tedious task requiring large samples and the development of new research strategies and methodologies