Advanced statistical tools for SNP arrays : signal calibration, copy number estimation and single array genotyping

Fluorescence bias in in signals from individual SNP arrays can be calibrated using linear models. Given the data, the system of equations is very large, so a specialized symbolic algorithm was developed. These models are also used to illustrate that genomic waves do not exist, but are merely an artifact of commonly used methods. Furthermore, a new semi-parametric, single array, approach to SNP genotyping is introduced and shown to be both effective and efficient. A refined algorithm for copy number estimation, using a zero-exponent norm is proposed, which performs well, as is illustrated by thorough comparisons with other methods. Indications that the signal calibration can improve (genotyping) results from lower quality samples are also discussed. A software suite that implements the above is described and illustrated.LEI Universiteit LeidenMultivariate analysis of psychological dat

Reliable Single Chip Genotyping with Semi-Parametric Log-Concave Mixtures

The common approach to SNP genotyping is to use (model-based) clustering per individual SNP, on a set of arrays. Genotyping all SNPs on a single array is much more attractive, in terms of flexibility, stability and applicability, when developing new chips. A new semi-parametric method, named SCALA, is proposed. It is based on a mixture model using semi-parametric log-concave densities. Instead of using the raw data, the mixture is fitted on a two-dimensional histogram, thereby making computation time almost independent of the number of SNPs. Furthermore, the algorithm is effective in low-MAF situations. Comparisons between SCALA and CRLMM on HapMap genotypes show very reliable calling of single arrays. Some heterozygous genotypes from HapMap are called homozygous by SCALA and to lesser extent by CRLMM too. Furthermore, HapMap's NoCalls (NN) could be genotyped by SCALA, mostly with high probability. The software is available as R scripts from the website www.math.leidenuniv.nl/~rrippe

Changes in face-specific neural processes explain reduced cuteness and approachability of infants with cleft lip

The current study investigated whether changes in the neural processing of faces of infants with a facial abnormality – a cleft lip – mediate effects of the cleft lip on judgments of infant cuteness and approachability. Event-related potentials (ERPs) in response to pictures of faces of healthy infants and infants with a cleft lip, and ratings of cuteness and approachability of these infant faces, were obtained from 30 females. Infants with a cleft lip were rated as less attractive (less cute and approachable) than healthy infants, and both the N170 and P2 components of the ERP were of reduced amplitude in response to pictures of infants with a cleft lip. Importantly, decreased configural processing of infant faces with a cleft lip, as evidenced by reduced N170 amplitudes, mediated the reduced attractiveness ratings for infants with a cleft lip compared to healthy infants. Our findings help elucidate the mechanisms behind the less favorable responses to infants with a cleft lip, highlighting the role of face-specific rather than domain-general neural processes

Attractiveness and neural processing of infant faces: Effects of a facial abnormality but not dopamine

Education and Child Studie

CBM language measures as indicators of foreign-language learning: technical adequacy of scores for secondary-school students

Education and Child Studie

The causal effect of household chaos on stress and caregiving: an experimental study

NWO016.145.360Education and Child Studie

Does sensory-processing sensitivity moderate the effect of household chaos on caregiver sensitivity? An experimental design

NWO016.145.360Education and Child Studie

Body mass index and peer victimization: a transactional model

Development Psychopathology in context: schoo

Rebutting existing misconceptions about multiple imputation as a method for handling missing data

Missing data is a problem that occurs frequently in many scientific areas. The most sophisticatedmethod for dealing with this problem is multiple imputation. Contrary to other methods, like listwise deletion, this method does not throw away information, and partly repairs the problem ofsystematic dropout. Although from a theoretical point of view multiple imputation is consideredto be the optimal method, many applied researchers are reluctant to use it because of persistentmisconceptions about this method. Instead of providing an(other) overview of missing data methods, or extensively explaining how multiple imputation works, this article aims specifically atrebutting these misconceptions, and provides applied researchers with practical arguments supporting them in the use of multiple imputation.Multivariate analysis of psychological dat

Attitudes of Secondary School STEM Teachers towards Supervising Research and Design Activities

Research and design activities are important focus points in international policies for secondary Science, Technology, Engineering and Mathematics (STEM) education. It is up to school teachers to implement and supervise these activities in the STEM classroom. However, not much is known about the attitudes teachers hold towards supervising research projects or design projects. In this study, a questionnaire to measure teacher attitudes towards supervising research activities and design activities in secondary school was completed by 130 Dutch teachers who taught the relatively new Dutch STEM subjects O&O (research and design) and NLT (nature, life, and technology). These integrated STEM subjects are project and context based and are taught in a limited number of schools. Important differences between these integrated STEM subjects are their student and teacher populations: NLT is taught in grades 10–12 by teachers with a qualification in a science subject, while O&O is taught in grades 7–12 and can be given by any teacher in secondary school. The results showed that on average, both O&O and NLT teachers had high self-efficacy scores on supervising research and design projects even when they had received no special education in doing so. Furthermore, the teachers in general viewed supervising research projects as a more relevant activity than supervising design. Since research and design activities are becoming more important in (inter)national curriculum standards, STEM teacher education and subsequent professional development should not only familiarize teachers with supervising research projects, but with design projects as well.Development Psychopathology in context: famil