On the Multiway Principal Component Analysis

Multiway data are becoming more and more common. While there are many approaches to extending principal component analysis (PCA) from usual data matrices to multiway arrays, their conceptual differences from the usual PCA, and the methodological implications of such differences remain largely unknown. This work aims to specifically address these questions. In particular, we clarify the subtle difference between PCA and singular value decomposition (SVD) for multiway data, and show that multiway principal components (PCs) can be estimated reliably in absence of the eigengaps required by the usual PCA, and in general much more efficiently than the usual PCs. Furthermore, the sample multiway PCs are asymptotically independent and hence allow for separate and more accurate inferences about the population PCs. The practical merits of multiway PCA are further demonstrated through numerical, both simulated and real data, examples

Software Piracy and Ethical Decision Making Behavior of Chinese Consumers

China has one of the highest software piracy rate in the world. It is important to understand consumers' ethical response to software piracy in the Chinese markets and design effective preventive strategies. This paper proposes a conceptual framework for an understanding of consumer ethical decision making. In the proposed framework, the transformation from legal problem recognition to ethical problem recognition is added to the traditional research framework and viewed as the first and most important step in consumer ethical decision making in regards to software piracy. The effects of two culture-related constructs— assumption of responsibility and attitude towards copyright laws on consumer ethical decision making— are examined and two propositions are made. The influence of Chinese culture and history on consumer ethical decision making is discussed. This paper contributes to our understanding of consumer ethical decision making in software piracy and provides new and constructive interpretations of the cultural influence

High-dimensional Inference for Generalized Linear Models with Hidden Confounding

Statistical inferences for high-dimensional regression models have been extensively studied for their wide applications ranging from genomics, neuroscience, to economics. In practice, there are often potential unmeasured confounders associated with both the response and covariates, leading to the invalidity of the standard debiasing methods. This paper focuses on a generalized linear regression framework with hidden confounding and proposes a debiasing approach to address this high-dimensional problem by adjusting for effects induced by the unmeasured confounders. We establish consistency and asymptotic normality for the proposed debiased estimator. The finite sample performance of the proposed method is demonstrated via extensive numerical studies and an application to a genetic dataset

A meta-data based method for DNA microarray imputation

BACKGROUND: DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. RESULTS: We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. CONCLUSION: Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available

microRNA-181a-5p impedes the proliferation, migration, and invasion of retinoblastoma cells by targeting the NRAS proto-oncogene

Objectives: Accumulating research have reported that microRNAs (miRNAs) play important roles in Retinoblastoma (RB). Nonetheless, the function and underlying mechanism of miR-181a-5p in RB remain ambiguous. Methods: The relative expression levels of miR-181a-5p and NRAS mRNA were detected by quantitative Reverse Transcription-Polymerase Chain Reaction (qRT-PCR). RB cell proliferation was measured using the Cell Counting Kit-8 (CCK-8) and 5′-Bromo-2′-deoxyuridine (BrdU) assays. Transwell assays and flow cytometry were performed to detect the migration, invasion, and apoptosis of RB cells. The interaction between miR-181a-5p and NRAS was explored using luciferase experiments, western blotting, and qRT-PCR. Results: miR-181a-5p expression was found to be decreased in RB tissues and cell lines, and its expression was correlated with unfavorable pathological features of the patients. In vitro experiments revealed that miR-181a-5p reduced RB cell proliferation, migration, and invasion while enhancing apoptosis. Further research confirmed that NRAS is a direct target of miR-181a-5p. miR-181a-5p inhibited NRAS expression at both the mRNA and protein levels. Co-transfection of pcDNA-NRAS or NRAS small interfering RNA (siRNA) reversed the effects of miR-181a-5p mimics or miR-181a-5p inhibitors on RB cells. Conclusion: miR-181a-5p was significantly downregulated during the development of RB, and it suppressed the malignant behaviors of RB cells by targeting NRAS

Successful radiofrequency ablation of a right posteroseptal accessory pathway through an anomalous inferior vena cava and azygos continuation in a patient with incomplete situs inversus

We present a 43-year-old patient with paroxysmal supraventricular tachycardia. In the process of catheter ablation, we found interruption of the inferior vena cava with azygos continuation with incomplete situs inversus. In this patient, we adopted the lower approach via the anomalous inferior vena cava and azygos continuation to achieve stability of radiofrequency catheter for right posteroseptal accessory pathway, and successfully abolished the preexcitation