Estimating False Discovery Proportion Under Arbitrary Covariance Dependence

Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are performed simultaneously to find if any SNPs are associated with some traits and those tests are correlated. When test statistics are correlated, false discovery control becomes very challenging under arbitrary dependence. In the current paper, we propose a novel method based on principal factor approximation, which successfully subtracts the common dependence and weakens significantly the correlation structure, to deal with an arbitrary dependence structure. We derive an approximate expression for false discovery proportion (FDP) in large scale multiple testing when a common threshold is used and provide a consistent estimate of realized FDP. This result has important applications in controlling FDR and FDP. Our estimate of realized FDP compares favorably with Efron (2007)'s approach, as demonstrated in the simulated examples. Our approach is further illustrated by some real data applications. We also propose a dependence-adjusted procedure, which is more powerful than the fixed threshold procedure.Comment: 51 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1012.439

Moderated Online Communities

Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators ’ incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from highreputation commentators can be inferior to that from low-reputation ones (reversed reputation). We finally investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result

Tradable Reputation and Online Economic Efficiency: A Field Experiment in Second Life

The online world has developed from a source of information to a complex economic and social environment. However, many online environments fail to function efficiently due to the lack of reliable reputation and anonymity of users. We propose a tradable reputation mechanism and conduct a virtual field experiment, using Second Life as an experimental platform, to investigate the role of reputation trading, based on our game theory analysis of the economic influence of tradable reputation. We introduce an avatar market that allows users to buy and sell avatars in terms of the reputation. Our main theoretical results show that reliable reputation is induced in a separating equilibrium where users are separated based on their ability in fulfilling tasks or transactions. We generate five hypotheses to test in the field experiment. We also describe a computer system that realizes the proposed mechanism as a basis for the field experiment

UBE2R2-AS1, as a prognostic marker of gastric cancer, promotes the malignant phenotype of gastric cancer cells

Background and Objectives. This study aimed to unveil the potential of UBE2R2-AS1 dysregulation in gastric cancer. In addition, its biological function was assessed. Materials and Methods. UBE2R2-AS1 expression was predicted in the ENCORI database. Paired gastric cancer and noncancerous tissues were collected. UBE2R2-AS1 expression was confirmed using RT-qPCR in our patient set. The association of UBE2R2-AS1 with the clinical data of patients was analyzed. Evaluation of the prognostic value of UBE2R2-AS1 was via Kaplan-Meier and Univariate/Multivariate Cox analyses. The effect of UBE2R2-AS1 on the cancer cell malignant phenotype was investigated. Results. Gastric cancer tissues and cells significantly overexpressed UBE2R2-AS1. UBE2R2-AS1 was significantly more abundant in unfavorable clinical pathology, including advanced TNM stage and lymph node metastasis. High expression of UBE2R2-AS1 predicted a poor prognosis with a hazard ratio (HR) of 3.041 and 2.805 after Univariate and Multivariate Cox analysis, respectively. UBE2R2-AS1 can act as a sponge for miR-302b-5p to promote cell proliferation, migration, and invasion of gastric cancer. Conclusion. The expression of UBE2R2-AS1 allowed the prognostic stratification of gastric cancer patients. UBE2R2-AS1 may accelerate the progression of gastric cancer via miR-302b-5

Novel Insights into the Role of the Cytoskeleton in Cancer

The cytoskeleton is a complex network of highly ordered intracellular filaments that plays a central role in controlling cell shape, division, functions, and interactions in human organs and tissues, but dysregulation of this network can contribute to numerous human diseases, including cancer. To clarify the various functions of the cytoskeleton and its role in cancer progression, in this chapter, we will discuss the microfilament (actin cytoskeleton), microtubule (β‐tubulin), and intermediate filament (keratins, cytokeratins, vimentin, and lamins) cytoskeletal structures; analyze the physiological functions of the cytoskeleton and its regulation of cell differentiation; and investigate the roles of the cytoskeleton in cancer progression, the epithelial‐mesenchymal transition process (EMT), and the mechanisms of multidrug resistance (MDR) in relation to the cytoskeleton. Importantly, the cytoskeleton, as a key regulator of the transcription and expression of many genes, is known to be involved in various physiological and pathological processes, which makes the cytoskeleton a novel and highly effective target for assessing the response to antitumor therapy in cancer