Medical Biomathematics and Biometrics Commons^™

Massively Parallel Nonparametric Regression, With An Application To Developmental Brain Mapping, Philip T. Reiss, Lei Huang, Yin-Hsiu Chen, Lan Huo, Thaddeus Tarpey, Maarten Mennes

Lei Huang

We propose a penalized spline approach to performing large numbers of parallel nonparametric analyses of either of two types: restricted likelihood ratio tests of a parametric regression model versus a general smooth alternative, and nonparametric regression. Compared with naively performing each analysis in turn, our techniques reduce computation time dramatically. Viewing the large collection of scatterplot smooths produced by our methods as functional data, we develop a clustering approach to summarize and visualize these results. Our approach is applicable to ultra-high-dimensional data, particularly data acquired by neuroimaging; we illustrate it with an analysis of developmental trajectories of functional connectivity at …

Varying-Smoother Models For Functional Responses, Philip T. Reiss, Lei Huang, Huaihou Chen, Stan Colcombe

Philip T. Reiss

This paper studies estimation of a smooth function f(x,v) when we are given functional responses of the form f(x, ·) + error, but scientific interest centers on the collection of functions f(·,v) for different v. The motivation comes from studies of human brain development, in which x denotes age whereas v refers to brain locations. Analogously to varying-coefficient models, in which the mean response is linear in x, the “varying-smoother” models that we consider exhibit nonlinear dependence on x that varies smoothly with v. We discuss three approaches to estimating varying-smoother models: (a) methods that employ a tensor product penalty; …

Paradoxical Results Of Adaptive False Discovery Rate Procedures In Neuroimaging Studies, Philip T. Reiss, Armin Schwartzman, Feihan Lu, Lei Huang, Erika Proal

Philip T. Reiss

Adaptive false discovery rate (FDR) procedures, which offer greater power than the original FDR procedure of Benjamini and Hochberg, are often applied to statistical maps of the brain. When a large proportion of the null hypotheses are false, as in the case of widespread effects such as cortical thinning throughout much of the brain, adaptive FDR methods can surprisingly reject more null hypotheses than not accounting for multiple testing at all—i.e., using uncorrected p-values. A straightforward mathematical argument is presented to explain why this can occur with the q-value method of Storey and colleagues, and a simulation study shows that …

Function-On-Scalar Regression With The Refund Package, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Smoothness Selection For Penalized Quantile Regression Splines, Philip T. Reiss, Lei Huang

Philip T. Reiss

Modern data-rich analyses may call for fitting a large number of nonparametric quantile regressions. For example, growth charts may be constructed for each of a collection of variables, to identify those for which individuals with a disorder tend to fall in the tails of their age-specific distribution; such variables might serve as developmental biomarkers. When such analyses are carried out by penalized spline smoothing, reliable automatic selection of the smoothing parameter is particularly important. We show that two popular methods for smoothness selection may tend to overfit when estimating extreme quantiles as a smooth function of a predictor such as …

Semiparametric Methods For Mapping Brain Development, Philip T. Reiss, Yin-Hsiu Chen, Lan Huo

Philip T. Reiss

No abstract provided.

Introducing Functional Data Analysis To Neuroimaging, And Vice Versa, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Massively Parallel Nonparametrics [Hds 2011 Slides], Philip T. Reiss, Lei Huang

Philip T. Reiss

No abstract provided.

Flexible Dependence Of Functional Responses On Scalar Predictors, Philip T. Reiss, Lei Huang

Philip T. Reiss

No abstract provided.

Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham

Lei Huang

Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship …

Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham

Philip T. Reiss

Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship …

Fast, Flexible Function-On-Scalar Regression, With An Application To Brain Development, Philip T. Reiss, Lei Huang

Philip T. Reiss

No abstract provided.

Functional Generalized Linear Models With Images As Predictors, Philip T. Reiss, R. Todd Ogden

Philip T. Reiss

Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this paper we present a theoretical justification for the use of principal components in functional regression. FPCR is then extended in two directions: from linear to the generalized linear modeling, and from univariate signal predictors to high-resolution image predictors. We show how to implement the method efficiently by adapting generalized additive model technology to the functional regression context. A technique is proposed for estimating simultaneous confidence bands for the coefficient function; in the neuroimaging setting, this yields a novel means to identify …

Semiparametric Analysis Of Recurrent Events: Artificial Censoring, Truncation, Pairwise Estimation And Inference, Debashis Ghosh

Debashis Ghosh

The analysis of recurrent failure time data from longitudinal studies can be complicated by the presence of dependent censoring. There has been a substantive literature that has developed based on an artificial censoring device. We explore in this article the connection between this class of methods with truncated data structures. In addition, a new procedure is developed for estimation and inference in a joint model for recurrent events and dependent censoring. Estimation proceeds using a mixed U-statistic based estimating function approach. New resampling-based methods for variance estimation and model checking are also described. The methods are illustrated by application to …

Multiple Loci Within The Major Histocompatibility Complex Confer Risk Of Psoriasis, Bing-Jian Feng, Liang-Dan Sun, Razieh Soltani-Arabshahi, Anne M. Bowcock, Rajan P. Nair, Philip Stuart, James T. Elder, Steven J. Schrodi, Ann B. Begovich, Goncalo R. Abecasis, Xue-Jun Zhang, Kristina P. Callis Duffin, Gerald G. Krueger, David E. Goldgar

Steven J Schrodi

Psoriasis is a common inflammatory skin disease characterized by thickened scaly red plaques. Previously we have performed a genome-wide association study (GWAS) on psoriasis with 1,359 cases and 1,400 controls, which were genotyped for 447,249 SNPs. The most significant finding was for SNP rs12191877, which is in tight linkage disequilibrium with HLA-Cw*0602, the consensus risk allele for psoriasis. However, it is not known whether there are other psoriasis loci within the MHC in addition to HLA-C. In the present study, we searched for additional susceptibility loci within the human leukocyte antigen (HLA) region through in-depth analyses of the GWAS data; …

Regression When The Predictors Are Images, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Genome-Wide Scan Reveals Association Of Psoriasis With Il-23 And Nf-B Pathways, Rajan P. Nair, Kristina C. Duffin, Cynthia Helms, Jun Ding, Philip E. Stuart, David Goldgar, Johann E. Gudjonsson, Yun Li, Trilokraj Tejasvi, Bing-Jiag Feng, Andreas Ruether, Stefan Schreiber, Michael Weichenthal, Dafna Gladman, Proton Rahman, Steven J. Schrodi, Sampath Prahalad, Stephen L. Guthery, Judith Fischer, Wilson Liao, Pui-Yan Kwok, Alan Menter, G Mark Lathrop, Carol A. Wise, Ann B. Begovich, John J. Voorhees, James T. Elder, Gerald G. Krueger, Anne M. Bowcock, Goncalo R. Abecasis

Steven J Schrodi

Psoriasis is a common immune-mediated disorder that affects the skin, nails and joints. To identify psoriasis susceptibility loci, we genotyped 438,670 SNPs in 1,409 psoriasis cases and 1,436 controls of European ancestry. We followed up 21 promising SNPs in 5,048 psoriasis cases and 5,041 controls. Our results provide strong support for the association of at least seven genetic loci and psoriasis (each with combined P < 5 10-8). Loci with confirmed association include HLA-C, three genes involved in IL-23 signaling (IL23A, IL23R, IL12B), two genes that act downstream of TNF- and regulate NF-B signaling (TNIP1, TNFAIP3) and two genes involved in the modulation of Th2 immune responses (IL4, IL13). Although the proteins encoded in these loci are known to interact biologically, we found no evidence for epistasis between associated SNPs. Our results expand the catalog of genetic loci implicated in psoriasis susceptibility and suggest priority targets for study in other auto-immune disorders.

A Fine Mapping Theorem To Refine Results From Association Genetics Studies, Steven J. Schrodi

Steven J Schrodi

No abstract provided.

Characterization Of Unknown Genetic Modifications Using High Throughput Sequencing And Computational Subtraction, Torstein Tengs

Dr. Torstein Tengs

Background

When generating a genetically modified organism (GMO), the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods that are reliably able to determine if an organism has been genetically altered if the nature of the modification is unknown.

Results

We show that the concept of computational subtraction can be used to identify transgenic cDNA sequences from genetically modified plants. Our datasets include 454-type sequences from a transgenic line of …

Simultaneous Confidence Bands For The Coefficient Function In Functional Regression, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Inferring Group Differences In Brain Connectivity From Functional Magnetic Resonance Images, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Reliability Of Functional Connectivity Networks: How Can We Assess It?, Philip T. Reiss

Philip T. Reiss

No abstract provided.

Functional Generalized Linear Models With Applications To Neuroimaging, Philip T. Reiss, R. Todd Ogden

Philip T. Reiss

No abstract provided.

A Large-Scale Rheumatoid Arthritis Genetic Study Identifies Association At Chr 9q33.2, Steven J. Schrodi

Steven J Schrodi

No abstract provided.

The Importance Of Experimental Design In Proteomic Mass Spectrometry Experiments: Some Cautionary Tales, Jeffrey S. Morris, Jianhua Hu, Kevin R. Coombes, Keith A. Baggerly

Jeffrey S. Morris

Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for the early diagnosis of cancer and other diseases. This approach has generated much excitement and has led to a large number of new experiments and vast amounts of new data. The data, derived at great expense, can have very little value if careful attention is not paid to the experimental design and analysis. Using examples from surfaceenhanced laser desorption/ionisation time-of-flight (SELDI-TOF) and matrix-assisted laser desorption–ionisation/time-of-flight (MALDI-TOF) experiments, we describe several experimental design issues that can corrupt a dataset. Fortunately, the problems we identify can be …

Food Based Approaches For A Healthy Nutrition In Africa, Mamoudou Hama Dicko

Pr. Mamoudou H. DICKO, PhD

The latest estimates of the FAO demonstrate the problems of the fight against hunger. These problems are manifested by the ever-increasing number of chronically undernourished people worldwide. Their numbers during the 1999-2001 period were estimated at about 840 million of which 798 million live in developing countries. Sub-Saharan Africa alone represented 198 million of those. In this part of Africa the prevalence of undernourishment ranges from 5-34%, causing growth retardation and insufficient weight gain among one third of the children under five years of age and resulting in a mortality of 5-15% among these children. Malnutrition resulting from undernourishment is …