A number of variable selection methods have been proposed involving nonconvex penalty functions. These methods, which include the smoothly clipped absolute deviation (SCAD) penalty and the minimax concave penalty (MCP), have been demonstrated to have attractive theoretical properties, but model fitting is not a straightforward task, and the resulting solutions may be unstable. Here, we demonstrate the potential of coordinate descent algorithms for fitting these models, establishing theoretical convergence properties and demonstrating that they are significantly faster than competing approaches. In addition, we demonstrate the utility of convexity diagnostics to determine regions of the parameter space in which the objective function is locally convex, even though the penalty is not. Our simulation study and data examples indicate that nonconvex penalties like MCP and SCAD are worthwhile alternatives to the lasso in many applications. In particular, our numerical results suggest that MCP is the preferred approach among the three methods.

Grouping structures arise naturally in many statistical modeling problems. Several methods have been proposed for variable selection that respect grouping structure in variables. Examples include the group LASSO and several concave group selection methods. In this article, we give a selective review of group selection concerning methodological developments, theoretical properties and computational algorithms. We pay particular attention to group selection methods involving concave penalties. We address both group selection and bi-level selection methods. We describe several applications of these methods in nonparametric additive models, semiparametric regression, seemingly unrelated regressions, genomic data analysis and genome wide association studies. We also highlight some issues that require further study.

SummaryVibrio parahaemolyticus senses surfaces via impeded rotation of its polar flagellum. We have exploited this surface-sensing mechanism to trick the organism into thinking it is on a surface when it is growing in liquid. This facilitated studies of global gene expression in a way that avoided many of the complications of surface-to-liquid comparisons, and illuminated~70 genes that respond to surface sensing per se. Almost all are surface-induced (not repressed) and encode swarming motility proteins, virulence factors or sensory enzymes involved with chemoreception and c-di-GMP signalling. Follow-up studies were performed to place the surfaceresponsive genes in a regulatory hierarchy. Mapping the hierarchy revealed two surprises about LafK, a transcriptional activator that until now has been considered to be the master regulator for the lateral flagellar system. First, LafK controls a more diverse set of genes than previously appreciated. Second, some laf genes are not under LafK control, which means LafK is not the master regulator after all. Additional experiments motivated by the transcriptome analyses revealed that growth on a surface lowers c-di-GMP levels and enhances cytotoxicity. Thus, we demonstrate that V. parahaemolyticus can invoke a programme of gene control upon encountering a surface and the specific identities of the surfaceresponsive genes are pertinent to colonization and pathogenesis.

Penalized regression is an attractive framework for variable selection problems. Often, variables possess a grouping structure, and the relevant selection problem is that of selecting groups, not individual variables. The group lasso has been proposed as a way of extending the ideas of the lasso to the problem of group selection. Nonconvex penalties such as SCAD and MCP have been proposed and shown to have several advantages over the lasso; these penalties may also be extended to the group selection problem, giving rise to group SCAD and group MCP methods. Here, we describe algorithms for fitting these models stably and efficiently. In addition, we present simulation results and real data examples comparing and contrasting the statistical properties of these methods.

The research examined whether performance by adult cochlear implant recipients on a variety of recognition and appraisal tests derived from real-world music could be predicted from technological, demographic, and life experience variables, as well as speech recognition scores. A representative sample of 209 adults implanted between 1985 and 2006 participated. Using multiple linear regression models and generalized linear mixed models, sets of optimal predictor variables were selected that effectively predicted performance on a test battery that assessed different aspects of music listening. These analyses established the importance of distinguishing between the accuracy of music perception and the appraisal of musical stimuli when using music listening as an index of implant success. Importantly, neither device type nor processing strategy predicted music perception or music appraisal. Speech recognition performance was not a strong predictor of music perception, and primarily predicted music perception when the test stimuli included lyrics. Additionally, limitations in the utility of speech perception in predicting musical perception and appraisal underscore the utility of music perception as an alternative outcome measure for evaluating implant outcomes. Music listening background, residual hearing (i.e., hearing aid use), cognitive factors, and some demographic factors predicted several indices of perceptual accuracy or appraisal of music. KeywordsCochlear implant; cognitive; music; speech perceptionThe cochlear implant (CI) is a prosthetic hearing device developed primarily to assist persons who are severely to profoundly deaf with verbal communication. The device picks up acoustic signals through an externally worn microphone, and these signals are then processed to filter and extract those components of sound critically important for speech perception. Those components are conveyed via electrical signals to an array of electrodes in the cochlea, resulting in electrical stimulation of the auditory nerve. This signal is then transmitted to the central Kate Gfeller, Department of Otolaryngology, 200 Hawkins Drive, 21201 PFP, Iowa City, IA 52242-1078 Portions of this article were presented in the keynote address for Music Perception for Cochlear Implant Workshops, University of Washington, Seattle, October 17, 2006 NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript auditory pathway for interpretation. Although the device does not provide an exact replica of normal hearing, the majority of postlingually deafened implant recipients using modern CIs score above 80% on high-context sentences in quiet listening conditions, even without visual cues (Wilson, 2000).Although CIs have been quite successful in providing implant recipients with speech perception, they are less effective in transmitting the fine structural features of sound that contribute to music perception (e.g., Gfeller et al, 2000aGfeller et al, , 2002aGfeller et al, , 2003Gfeller et al, , 2005Gfeller et al, , 2007Le...

The continuous replacement of neurons in the olfactory epithelium provides an advantageous model for investigating neuronal differentiation and maturation. By calculating the relative enrichment of every mRNA detected in samples of mature mouse olfactory sensory neurons (OSNs), immature OSNs, and the residual population of neighboring cell types, and then comparing these ratios against the known expression patterns of >300 genes, enrichment criteria that accurately predicted the OSN expression patterns of nearly all genes were determined. We identified 847 immature OSN-specific and 691 mature OSN-specific genes. The control of gene expression by chromatin modification and transcription factors, and neurite growth, protein transport, RNA processing, cholesterol biosynthesis, and apoptosis via death domain receptors, were overrepresented biological processes in immature OSNs. Ion transport (ion channels), presynaptic functions, and cilia-specific processes were overrepresented in mature OSNs. Processes overrepresented among the genes expressed by all OSNs were protein and ion transport, ER overload response, protein catabolism, and the electron transport chain. To more accurately represent gradations in mRNA abundance and identify all genes expressed in each cell type, classification methods were used to produce probabilities of expression in each cell type for every gene. These probabilities, which identified 9,300 genes expressed in OSNs, were 96% accurate at identifying genes expressed in OSNs and 86% accurate at discriminating genes specific to mature and immature OSNs. This OSN gene database not only predicts the genes responsible for the major biological processes active in OSNs, but also identifies thousands of never before studied genes that support OSN phenotypes.

Ga-DOTATOC, a somatostatin receptor-targeted ligand, has been used clinically in Europe over the past decade for imaging neuroendocrine tumors (NETs). It appears to be quite sensitive and effective for clinical management decision making. This metaanalysis summarizes the efficacy of Ga-DOTATOC for several distinct indications and is intended to support approval of this agent by the U.S. Food and Drug Administration. The major electronic medical databases were searched for relevant papers over the period from January 2001 to November 2015. Papers were selected for review in 3 categories: clinical trials that reported sensitivity and specificity, comparison studies with In-octreotide, and change of management studies. All the eligible papers underwent Quality Assessment of Diagnostic Accuracy Studies (QUADAS) assessment, which was useful in the final selection of papers for review. The initial search yielded 468 papers. After detailed evaluation, 17 papers were finally selected. Five types of studies emerged: workup of patients with symptoms and biomarker findings suggestive of NET, but with negative conventional imaging (3 papers, yield was only 13%); sensitivity (12 papers; sensitivity, 92%) and specificity (7 papers; specificity, 82%); identification of site of unknown primary in patients with metastatic NET (4 papers, yield was 44%); impact on subsequent NET patient management (4 papers, change in management in 51%); and comparison with In-octreotide (2 papers, sensitivity of DOTATOC on a per-lesion basis was 100%, forIn-octreotide it was 78.2%; specificity was not available). Safety was not explicitly addressed in any study, but there were no reports of adverse events. Ga-DOTATOC is useful for evaluating the presence and extent in disease for staging and restaging and for assisting in treatment decision making for patients with NET. It is also effective in locating the site of an unknown primary in NET patients who present with metastatic NET, but no known primary tumor. It also appears to be more accurate thanIn-octreotide. Although Ga-DOTATOC would seem to be useful in evaluating patients with suggestive symptoms and biomarker findings, it does not perform well in this setting and has low yield. Overall, it appears to be an excellent imaging agent to assess patients with known NET and frequently leads to a change in management.

In many applications, covariates possess a grouping structure that can be incorporated into the analysis to select important groups as well as important members of those groups. One important example arises in genetic association studies, where genes may have several variants capable of contributing to disease. An ideal penalized regression approach would select variables by balancing both the direct evidence of a feature's importance as well as the indirect evidence offered by the grouping structure. This work proposes a new approach we call the group exponential lasso (GEL) which features a decay parameter controlling the degree to which feature selection is coupled together within groups. We demonstrate that the GEL has a number of statistical and computational advantages over previously proposed group penalties such as the group lasso, group bridge, and composite MCP. Finally, we apply these methods to the problem of detecting rare variants in a genetic association study.