One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has been developed to provide users with a choice of multiple changepoint search methods to use in conjunction with a given changepoint method and in particular provides an implementation of the recently proposed PELT algorithm. This article describes the search methods which are implemented in the package as well as some of the available test statistics whilst highlighting their application with simulated and practical examples. Particular emphasis is placed on the PELT algorithm and how results differ from the binary segmentation approach.

/pdf/changepoint-an-r-package-for-changepoint-analysis-4f9vs6okd3.pdf

changepoint: An R Package for Changepoint Analysis

Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.

/pdf/scanning-the-horizon-towards-transparent-and-reproducible-oifq7uu09d.pdf

Scanning the horizon: towards transparent and reproducible neuroimaging research

Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation

Sequence census methods like ChIP-seq now produce an unprecedented amount of genome-anchored data. We have developed an integrative method to identify patterns from multiple experiments simultaneously while taking full advantage of high-resolution data, discovering joint patterns across different assay types. We apply this method to ENCODE chromatin data for the human chronic myeloid leukemia cell line K562, including ChIP-seq data on covalent histone modifications and transcription factor binding, and DNase-seq and FAIRE-seq readouts of open chromatin. In an unsupervised fashion, we identify patterns associated with transcription start sites, gene ends, enhancers, CTCF elements, and repressed regions. The method yields a model which elucidates the relationship between assay observations and functional elements in the genome. This model identifies sequences likely to affect transcription, and we verify these predictions in laboratory experiments. We have made software and an integrative genome browser track freely available (noble.gs.washington.edu/proj/segway/).

/pdf/unsupervised-pattern-discovery-in-human-chromatin-structure-njvwi5mmap.pdf

Unsupervised pattern discovery in human chromatin structure through genomic segmentation

Selective review of offline change point detection methods

Barry and Hartigan (1993) propose a Bayesian analysis for change point problems. We provide a brief summary of selected work on change point problems, both preceding and following Barry and Hartigan. We outline Barry and Hartigan's approach and offer a new R package, bcp (Erdman and Emerson 2007), implementing their analysis. We discuss two frequentist alternatives to the Bayesian analysis, the recursive circular binary segmentation algorithm (Olshen and Venkatraman 2004) and the dynamic programming algorithm of (Bai and Perron 2003). We illustrate the application of bcp with economic and microarray data from the literature.

/pdf/bcp-an-r-package-for-performing-a-bayesian-analysis-of-4g7adgal0r.pdf

bcp: An R Package for Performing a Bayesian Analysis of Change Point Problems

Methodology extending nonparametric goodness-of-fit tests to discrete null distributions has existed for several decades. However, modern statistical software has generally failed to provide this methodology to users. We offer a revision of R’s ks.test() function and a new cvm.test() function that fill this need in the R language for two of the most popular nonparametric goodness-of-fit tests. This paper describes these contributions and provides examples of their usage. Particular attention is given to various numerical issues that arise in their implementation.

/pdf/nonparametric-goodness-of-fit-tests-for-discrete-null-1l5zzvptnx.pdf

Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions

Pulmonary infection with an exaggerated inflammatory response is the major cause of morbidity and mortality in cystic fibrosis (CF). The objective of this study was to determine whether differences in the innate immune system underlie the exaggerated immune response in CF. We established a model that recapitulates the exaggerated immune response in a CF mouse model by exposure to Pseudomonas aeruginosa LPS and assessed the pulmonary cellular and cytokine responses of wild-type (WT) and CF mice. Compared with WT mice, CF mice had increased numbers of neutrophils and increased proinflammatory cytokines in their bronchoalveolar lavage fluid after LPS exposure. Based on the increased levels of IL-1alpha, IL-6, granulocyte colony-stimulating factor (G-CSF), and keratinocyte chemoattractant, all of which are known to be produced by macrophages, we tested whether two populations of macrophages, bone marrow-derived macrophages and alveolar macrophages, directly contribute to the elevated cytokine response of CF mice to LPS. After in vitro stimulation of bone marrow-derived macrophages and alveolar macrophages with LPS, IL-1alpha, IL-6, G-CSF, and monocyte chemoattractant protein-1 were higher in CF compared with WT cell supernatants. Quantitative analyses for IL-6 and keratinocyte chemoattractant revealed that LPS-stimulated CF macrophages have higher mRNA and intracellular protein levels compared with WT macrophages. Our data support the hypothesis that macrophages play a role in the exuberant cytokine production and secretion that characterizes CF, suggesting that the macrophage response may be an important therapeutic target for decreasing the morbidity of CF lung disease.

/pdf/macrophages-directly-contribute-to-the-exaggerated-24d4afatwb.pdf

Macrophages Directly Contribute to the Exaggerated Inflammatory Response in Cystic Fibrosis Transmembrane Conductance Regulator−/− Mice

Individuals who are unaware of the price do not derive more enjoyment from more expensive wine. In a sample of more than 6,000 blind tastings, we fi that the correlation between price and overall rating is small and negative, suggesting that individuals on average enjoy more expensive wines slightly less. For individuals with wine training, however, we fiindications of a non-negative relationship between price and enjoyment. Our results are robust to the inclusion of individual fi xed effects, and are not driven by outliers: when omitting the top and bottom deciles of the price distribution, our qualitative results are strengthened, and the statistical signifi cance is improved further. These fi ndings suggest that non-expert wine consumers should not anticipate greater enjoyment of the intrinsic qualities of a wine simply because it is expensive or is appreciated by experts. (JEL Classifi cation: L15, L66, M30, Q13)

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Do More Expensive Wines Taste Better? Evidence from a Large Sample of Blind Tastings*

https://espace.library.uq.edu.au/view/UQ:328270/Shehzad.pdf

John W. Emerson

Papers

bcp: An R Package for Performing a Bayesian Analysis of Change Point Problems

Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions

Macrophages Directly Contribute to the Exaggerated Inflammatory Response in Cystic Fibrosis Transmembrane Conductance Regulator−/− Mice

Do More Expensive Wines Taste Better? Evidence from a Large Sample of Blind Tastings*

A multivariate distance-based analytic framework for connectome-wide association studies.