Microarrays, Empirical Bayes and the Two-Groups Model

The classic frequentist theory of hypothesis testing developed by Neyman, Pearson and Fisher has a claim to being the twentieth century's most influential piece of applied mathematics. Something new is happening in the twenty-first century: high-throughput devices, such as microarrays, routinely require simultaneous hypothesis tests for thousands of individual cases, not at all what the classical theory had in mind. In these situations empirical Bayes information begins to force itself upon frequentists and Bayesians alike. The two-groups model is a simple Bayesian construction that facilitates empirical Bayes analysis. This article concerns the interplay of Bayesian and frequentist ideas in the two-groups setting, with particular attention focused on Benjamini and Hochberg's False Discovery Rate method. Topics include the choice and meaning of the null hypothesis in large-scale testing situations, power considerations, the limitations of permutation methods, significance testing for groups of cases (such as pathways in microarray studies), correlation effects, multiple confidence intervals and Bayesian competitors to the two-groups model.Comment: This paper commented in: [arXiv:0808.0582], [arXiv:0808.0593], [arXiv:0808.0597], [arXiv:0808.0599]. Rejoinder in [arXiv:0808.0603]. Published in at http://dx.doi.org/10.1214/07-STS236 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Are a set of microarrays independent of each other?

Having observed an $m\times n$ matrix $X$ whose rows are possibly correlated, we wish to test the hypothesis that the columns are independent of each other. Our motivation comes from microarray studies, where the rows of $X$ record expression levels for $m$ different genes, often highly correlated, while the columns represent $n$ individual microarrays, presumably obtained independently. The presumption of independence underlies all the familiar permutation, cross-validation and bootstrap methods for microarray analysis, so it is important to know when independence fails. We develop nonparametric and normal-theory testing methods. The row and column correlations of $X$ interact with each other in a way that complicates test procedures, essentially by reducing the accuracy of the relevant estimators.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS236 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Legal aid reforms may leave welfare, employment and health disputes unresolved and actually increase the demand for court and tribunal hearings

The Legal Aid, Sentencing and Punishment of Offenders Bill currently before parliament is intended, in part, to reduce demand for ‘costly litigation’ in key areas of civil law. However, recent research suggests that aspects of the Bill may actually work against this aim. Laura Bradley warns the Ministry of Justice to seriously consider the risk that some of the most controversial reforms may in fact increase demand for court and tribunal hearings, and reduce the chance that people’s everyday civil legal disputes end with agreement being reached

Book Review: Christ Across the Ganges: Hindu Responses to Jesus

A review of Christ Across the Ganges: Hindu Responses to Jesus by Sandy Bharat

Book Review: Brahman and Person: Essays by Richard De Smet

Bradley Malkovsky\u27s review of Brahman and Person: Essays by Richard De Smet, edited by Ivo Coelho

Two Poems

Poetry by Nicholas Bradle

The Cost of Care: New Insights into Healthcare Spending Growth

[Excerpt] The Bureau of Labor Statistics (BLS) is celebrating the first anniversary of experimental disease-based price indexes, which adjust expenditures on disease for inflation. Statistical agencies have long collected price information on medical procedures, drugs, equipment, and services, but the cost of treating a patient is typically some combination of these goods and services. Many users of the Federal Statistical System have asked that medical care spending be reported on a disease basis. Creating price indexes on a disease basis helps provide greater understanding of the cost of care for a given condition. The indexes are the result of a long-term research effort by staff in the BLS Office of Prices and Living Conditions. Using existing data products, we met the need for a new product, without incurring more data collection expenses. We construct the experimental indexes using two publicly available datasets: 1) the monthly producer price index (PPI) and consumer price index (CPI) published by BLS and 2) the Medical Expenditure Panel Survey (MEPS) published by the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services. The monthly BLS data allow our experimental disease-based price indexes to be timely. MEPS supplies data on the use of medical service and products for the treatment of each disease. After a year of constructing the experimental disease-based index we reveal the wealth of information that the data show. This Beyond the Numbers article examines the reasons for reporting by disease rather than by service and explains the reasons behind the spending growth for each disease

Biocatalytic Synthesis of Stereospecific Triketide Lactones using Polyketide Synthases

Polyketide synthases are modular enzymes that create and modify large acyl chains. The domains and modules of polyketide synthases allow us to create molecules that resemble naturally occurring products by applying a biocatalytic in vitro in vivo approach to a diketide acyl chain. We showed that a triketide lactone of desired stereochemistry could be made using a domain and module from the polyketide synthase found in Saccharopolyspora erythraea, 6-Deoxyerythronolide B Synthase. Future projects will explore this approach using different domains and modules.Biochemistr