Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data

<p>Abstract</p> <p>Background</p> <p>Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differentially expressed in time-course data, measured between different biological conditions. These differentially expressed genes can reveal the changes in biological process due to the change in condition which is essential to understand differences in dynamics.</p> <p>Results</p> <p>In this paper, we propose a novel method for finding differentially expressed genes in time-course data and across biological conditions (say <it>C</it>₁and <it>C</it>₂). We model the expression at <it>C</it>₁using Principal Component Analysis and represent the expression profile of each gene as a linear combination of the dominant Principal Components (PCs). Then the expression data from <it>C</it>₂is projected on the developed PCA model and scores are extracted. The difference between the scores is evaluated using a hypothesis test to quantify the significance of differential expression. We evaluate the proposed method to understand differences in two case studies (1) the heat shock response of wild-type and HSF1 knockout mice, and (2) cell-cycle between wild-type and Fkh1/Fkh2 knockout Yeast strains.</p> <p>Conclusion</p> <p>In both cases, the proposed method identified biologically significant genes.</p

The Happiest Kids on Earth : Gender Equality and Adolescent Life Satisfaction in Europe and North America

Cross-national differences in adolescent life satisfaction in Europe and North America are consistent, but remain poorly understood. While previous studies have predominantly focused on the explanatory role of economic factors, such as national wealth and income equality, they revealed weak associations, at most. This study examines whether societal gender equality can explain the observed cross-national variability in adolescent life satisfaction. Based on the assumption that gender equality fosters a supportive social context, for example within families through a more equal involvement of fathers and mothers in child care tasks, adolescent life satisfaction was expected to be higher in more gender-equal countries. To test this hypothesis, national-level data of gender equality (i.e., women’s share in political participation, decision making power, economic participation and command over resources) were linked to data from 175,470 adolescents aged 11–16 years old (Mage = 13.6, SD = 1.64, 52% girls) from 34 European and North American countries involved in the 2009/10 Health Behaviour in School-aged Children (HBSC) study. Results of linear multilevel regression analyses indicate that adolescents in countries with relatively high levels of gender equality report higher life satisfaction than their peers in countries with lower levels of gender equality. The association between gender equality and adolescent life satisfaction remained significant after controlling for national wealth and income equality. It was equally strong for boys and girls. Moreover, the association between gender equality and life satisfaction was explained by social support in the family, peer and school context. This analysis suggests that gender equality fosters social support among members of a society, which in turn contributes to adolescent life satisfaction. Thus, promoting gender equality is likely to benefit all members of a society; not just by giving equal rights to women and girls, but also by fostering a supportive social climate for all