Incorporating a New Summary Statistic into the Min–Max Approach: A Min–Max–Median, Min–Max–IQR Combination of Biomarkers for Maximising the Youden Index

Linearly combining multiple biomarkers is a common practice that can provide a better diagnostic performance. When the number of biomarkers is sufficiently high, a computational burden problem arises. Liu et al. proposed a distribution-free approach (min–max approach) that linearly combines the minimum and maximum values of the biomarkers, involving only a single coefficient search. However, the combination of minimum and maximum biomarkers alone may not be sufficient in terms of discrimination. In this paper, we propose a new approach that extends that of Liu et al. by incorporating a new summary statistic, specifically, the median or interquartile range (min–max–median and min–max–IQR approaches) in order to find the optimal combination that maximises the Youden index. Although this approach is more computationally intensive than the one proposed by Liu et al, it includes more information and the number of parameters to be estimated remains reasonable. We compare the performance of the proposed approaches (min–max–median and min–max–IQR) with the min–max approach and logistic regression. For this purpose, a wide range of different simulated data scenarios were explored. We also apply the approaches to two real datasets (Duchenne Muscular Dystrophy and Small for Gestational Age).

MungeSumstats: A Bioconductor package for the standardisation and quality control of many GWAS summary statistics

Motivation Genome-wide association studies (GWAS) summary statistics have popularised and accelerated genetic research. However, a lack of standardisation of the file formats used has proven problematic when running secondary analysis tools or performing meta-analysis studies. Results To address this issue, we have developed MungeSumstats, a Bioconductor R package for the standardisation and quality control of GWAS summary statistics. MungeSumstats can handle the most common summary statistic formats, including variant call format (VCF) producing a reformatted, standardised, tabular summary statistic file, VCF or R native data object. Availability MungeSumstats is available on Bioconductor (v 3.13) and can also be found on Github at: https://neurogenomics.github.io/MungeSumstats Supplementary information The analysis deriving the most common summary statistic formats is available at: https://al-murphy.github.io/SumstatFormats

Aplikasi model Rasch pada adaptasi skala personal fable remaja di Jawa Barat

The research aims to examine the reliability and validity of a new personal fable scale in West Java adapted from Lapsley dkk. (1989). New Personal Fable Scale consists of 46 items with 3 dimensions: invulnerability, omnipotence, and personal uniqueness. The subjects of this study were 489 adolescents in West Java. The Rasch Model analysis from summary statistics, scalograms, item measure, person measure, and dimensionality map shows that this scale’s model is a good fit. The convergent validity test shows that the new personal fable scale which is adapted to Bahasa is valid. Reliability with a Cronbach Alpha method is 0,8 which means this scale is reliable. The results indicate that there are several items that need to be improved. This research provides information about the psychometric properties of egocentrism in adolescent especially personal fable in West Java.Keywords: Adolescents; Egocentrism; Personal Fable; Reliability; Validity Abstrak Penelitian ini bertujuan untuk melihat reliabilitas dan validitas alat ukur personal fable adaptasi secara bahasa yang disesuaikan dengan faktor kultur budaya di Jawa Barat yang berasal dari Lapsley dkk. (1989). Alat ukur personal fable terdiri dari 46 aitem dengan 3 dimensi yaitu invulnerability, omnipotence, dan personal uniqueness. Subjek dari penelitian ini adalah 489 remaja di Jawa Barat. Hasil uji model Rasch dilihat dari analisis summary statistic, scalogram, item measure, person measure, dan dimensionality map menyatakan bahwa alat ukur fit dengan model. Alat ukur adaptasi ini dikatakan valid dilihat dari hasil uji validitas konvergen. Reliabilitas yang dianalisis dengan koefisien Alpha Cronbach sebesar 0,8 menunjukkan bahwa alat ukur adaptasi ini reliabel. Hasil analisis data menunjukkan adanya beberapa aitem yang perlu diperbaiki dalam rangka penyempurnaan alat ukur adaptasi. Penelitian ini dapat memberikan informasi dan memperkaya referensi keilmuan psikologi dan psikometri pada konstruk egosentrisme remaja khususnya personal fable di Jawa Barat.Kata kunci: Egosentrisme; Personal Fable; Remaja; Reliabilitas; Validitas

MungeSumstats: A Bioconductor package for the standardisation and quality control of many GWAS summary statistics

Genome-wide association studies (GWAS) summary statistics have democratised and accelerated genetic research. However, a lack of standardisation of the file formats used has proven problematic when running secondary analysis tools or performing meta-analysis studies. To address these issues, we have developed MungeSumstats, a Bioconductor R package for the standardisation and quality control of GWAS summary statistics. MungeSumstats can handle the most common summary statistic formats, including variant call format (VCF) producing a reformatted, standardised, tabular summary statistic file.

An Integrative Transcriptome-Wide Analysis of Amyotrophic Lateral Sclerosis for the Identification of Potential Genetic Markers and Drug Candidates

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative neuromuscular disease. Although genome-wide association studies (GWAS) have successfully identified many variants significantly associated with ALS, it is still difficult to characterize the underlying biological mechanisms inducing ALS. In this study, we performed a transcriptome-wide association study (TWAS) to identify disease-specific genes in ALS. Using the largest ALS GWAS summary statistic (n = 80,610), we identified seven novel genes using 19 tissue reference panels. We conducted a conditional analysis to verify the genes’ independence and to confirm that they are driven by genetically regulated expressions. Furthermore, we performed a TWAS-based enrichment analysis to highlight the association of important biological pathways, one in each of the four tissue reference panels. Finally, utilizing a connectivity map, a database of human cell expression profiles cultured with bioactive small molecules, we discovered functional associations between genes and drugs to identify 15 bioactive small molecules as potential drug candidates for ALS. We believe that, by integrating the largest ALS GWAS summary statistic with gene expression to identify new risk loci and causal genes, our study provides strong candidates for molecular basis experiments in ALS.

High Leverage Practices in Special Education Synthesis Coding Protocol

The purpose of document is to provide readers with the coding protocol that authors used to code 76 meta-analyses focused on students with or at-risk of disabilities. All of the included meta-analyses provided a summary statistic related to at least one of the High Leverage Practices (HLPs; McLeskey et al., 2017). ). The purpose of the systematic review of meta-analyses was to provide an initial investigation of the evidence supporting the effectiveness of the HLPs for students with, or at-risk for, a disability. This code book contains variable names, code options, and code definitions related to basic study information (i.e., authors, year of publication, journal), the details of each study, participant demographics, HLPs included in each study, and summary statistics. The mean interrater reliability across all codes using this protocol was 88% (range across categories = 84%–97%)

Convergence in models of misspecified learning

We establish convergence of beliefs and actions in a class of one‐dimensional learning settings in which the agent's model is misspecified, she chooses actions endogenously, and the actions affect how she misinterprets information. Our stochastic‐approximation‐based methods rely on two crucial features: that the state and action spaces are continuous, and that the agent's posterior admits a one‐dimensional summary statistic. Through a basic model with a normal–normal updating structure and a generalization in which the agent's misinterpretation of information can depend on her current beliefs in a flexible way, we show that these features are compatible with a number of specifications of how exactly the agent updates. Applications of our framework include learning by a person who has an incorrect model of a technology she uses or is overconfident about herself, learning by a representative agent who may misunderstand macroeconomic outcomes, and learning by a firm that has an incorrect parametric model of demand.

Saccadic scanpath length: an index for human threat conditioning

Threat-conditioned cues are thought to capture overt attention in a bottom-up process. Quantification of this phenomenon typically relies on cue competition paradigms. Here, we sought to exploit gaze patterns during exclusive presentation of a visual conditioned stimulus, in order to quantify human threat conditioning. To this end, we capitalized on a summary statistic of visual search during CS presentation, scanpath length. During a simple delayed threat conditioning paradigm with full-screen monochrome conditioned stimuli (CS), we observed shorter scanpath length during CS+ compared to CS- presentation. Retrodictive validity, i.e., effect size to distinguish CS+ and CS-, was maximized by considering a 2-s time window before US onset. Taking into account the shape of the scan speed response resulted in similar retrodictive validity. The mechanism underlying shorter scanpath length appeared to be longer fixation duration and more fixation on the screen center during CS+ relative to CS- presentation. These findings were replicated in a second experiment with similar setup, and further confirmed in a third experiment using full-screen patterns as CS. This experiment included an extinction session during which scanpath differences appeared to extinguish. In a fourth experiment with auditory CS and instruction to fixate screen center, no scanpath length differences were observed. In conclusion, our study suggests scanpath length as a visual search summary statistic, which may be used as complementary measure to quantify threat conditioning with retrodictive validity similar to that of skin conductance responses.

Inferring the Effect of Species Interactions on Trait Evolution

Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein–Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been developed, particularly involving competition where abiotic factors pull species toward an optimal trait value and competitive interactions drive the trait values apart. However, these models assume a fitness function rather than derive it from population dynamics and they do not consider dynamics of the trait variance. Here, we develop a general coherent trait evolution framework where the fitness function is based on a model of population dynamics, and therefore it can, in principle, accommodate any type of species interaction. We illustrate our framework with a model of abundance-dependent competitive interactions against a macroevolutionary background encoded in a phylogenetic tree. We develop an inference tool based on Approximate Bayesian Computation and test it on simulated data (of traits at the tips). We find that inference performs well when the diversity predicted by the parameters equals the number of species in the phylogeny. We then fit the model to empirical data of baleen whale body lengths, using three different summary statistics, and compare it to a model without population dynamics and a model where competition depends on the total metabolic rate of the competitors. We show that the unweighted model performs best for the least informative summary statistic, while the model with competition weighted by the total metabolic rate fits the data slightly better than the other two models for the two more informative summary statistics. Regardless of the summary statistic used, the three models substantially differ in their predictions of the abundance distribution. Therefore, data on abundance distributions will allow us to better distinguish the models from one another, and infer the nature of species interactions. Thus, our framework provides a conceptual approach to reveal species interactions underlying trait evolution and identifies the data needed to do so in practice. [Approximate Bayesian computation; competition; phylogeny; population dynamics; simulations; species interaction; trait evolution.]