LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data.

abstract：:Usually, a pedigree is sampled and included in the sample that is analyzed after following a predefined non-random sampling design comprising several specific procedures. To obtain a pedigree analysis result free from the bias caused by the sampling procedures, a correction is applied to the pedigree likelihood. The s...

journal_title：Statistical applications in genetics and molecular biology

authors： Ginsburg E,Malkin I,Elston RC

更新日期：2003-01-01 00:00:00

abstract：:In recent years, alignment-free methods have been widely applied in comparing genome sequences, as these methods compute efficiently and provide desirable phylogenetic analysis results. These methods have been successfully combined with hierarchical clustering methods for finding phylogenetic trees. However, it may no...

journal_title：Statistical applications in genetics and molecular biology

authors： Huang HH,Girimurugan SB

更新日期：2019-02-15 00:00:00

abstract：:An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical analysis in such applications is dimension reduction. This paper provides a comparison study of three dimension reduction tech...

journal_title：Statistical applications in genetics and molecular biology

authors： Dai JJ,Lieu L,Rocke D

更新日期：2006-01-01 00:00:00

abstract：:Germline mosaicism is a genetic condition in which some germ cells of an individual contain a mutation. This condition violates the assumptions underlying classic genetic analysis and may lead to failure of such analysis. In this work we extend the statistical model used for genetic linkage analysis in order to incorp...

journal_title：Statistical applications in genetics and molecular biology

authors： Weissbrod O,Geiger D

更新日期：2011-10-04 00:00:00

abstract：:Reproducibility of disease signatures and clinical biomarkers in multi-omics disease analysis has been a key challenge due to a multitude of factors. The heterogeneity of the limited sample, various biological factors such as environmental confounders, and the inherent experimental and technical noises, compounded wit...

journal_title：Statistical applications in genetics and molecular biology

authors： Liang Y,Kelemen A,Kelemen A

更新日期：2019-05-11 00:00:00

abstract：:Recent analytic and technological breakthroughs have set the stage for genome-wide linkage disequilibrium studies to map disease-susceptibility variants. This paper discusses a probabilistic methodology for making disease-mapping inferences in large-scale case-control genetic studies. The semi-Bayesian approach promot...

journal_title：Statistical applications in genetics and molecular biology

authors： Schrodi SJ

更新日期：2005-01-01 00:00:00

abstract：:The genetic control of a complex trait can be studied by testing and mapping the genotypes of the underlying quantitative trait loci (QTLs) through their associations with observable marker genotypes. All existing statistical methods for QTL mapping assume an equilibrium population, allowing marker-QTL associations to...

journal_title：Statistical applications in genetics and molecular biology

authors： Wu S,Yang J,Wu R

更新日期：2010-01-01 00:00:00

abstract：:In candidate gene association studies, usually several elementary hypotheses are tested simultaneously using one particular set of data. The data normally consist of partly correlated SNP information. Every SNP can be tested for association with the disease, e.g., using the Cochran-Armitage test for trend. To account ...

journal_title：Statistical applications in genetics and molecular biology

authors： Elsäβer A,Victor A,Hommel G

更新日期：2011-01-01 00:00:00

abstract：:In a hidden Markov model, one "estimates" the state of the hidden Markov chain at t by computing via the forwards-backwards algorithm the conditional distribution of the state vector given the observed data. The covariance matrix of this conditional distribution measures the information lost by failure to observe dire...

journal_title：Statistical applications in genetics and molecular biology

authors： Siegmund DO,Yakir B

更新日期：2007-01-01 00:00:00

abstract：:Multiple testing procedures are commonly used in gene expression studies for the detection of differential expression, where typically thousands of genes are measured over at least two experimental conditions. Given the need for powerful testing procedures, and the attendant danger of false positives in multiple testi...

journal_title：Statistical applications in genetics and molecular biology

authors： Green GH,Diggle PJ

更新日期：2007-01-01 00:00:00

abstract：:Multiple branching trees have been used to model the acquisition of HIV drug resistance mutations, and several different algorithms have been developed to construct the tree set that best describes the data. These algorithms have mainly focused on the structure of the tree set. The focal point of this paper is estimat...

journal_title：Statistical applications in genetics and molecular biology

authors： Healy BC,DeGruttola VG,Hu C

更新日期：2008-01-01 00:00:00

abstract：:Integrative analysis of copy number and gene expression data can help in understanding the cis and trans effect of copy number aberrations on transcription levels of genes involved in a pathway. To analyse how these copy number mediated gene-gene interactions differ between groups of samples we propose a new method, n...

journal_title：Statistical applications in genetics and molecular biology

authors： Chaturvedi N,Menezes RX,Goeman JJ,Wieringen WV

更新日期：2018-07-31 00:00:00

abstract：:Locus heterogeneity is one of the most important issues in gene mapping and can cause significant reductions in statistical power for gene mapping, yet no research to date has provided power and sample size calculations for family-based association methods in the presence of locus heterogeneity. The purpose of this re...

journal_title：Statistical applications in genetics and molecular biology

authors： Chen C,Yang G,Buyske S,Matise T,Finch SJ,Gordon D

更新日期：2009-01-01 00:00:00

abstract：:In this paper, we explore the use of M-quantile regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions. In particular, we consider the application of temporal gene expression data. Here, the aim is to detect genes whose temporal...

journal_title：Statistical applications in genetics and molecular biology

authors： Vinciotti V,Yu K

更新日期：2009-01-01 00:00:00

abstract：:The approach adopted involved two-stages. First the 11205 measurements in the mass spectrometry data were reduced to 14 scores by a principal component analysis of the centered but otherwise untreated and unscaled data matrix. Then a linear classifier was derived by linear discriminant analysis using these 14 scores a...

journal_title：Statistical applications in genetics and molecular biology

authors： Fearn T

更新日期：2008-01-01 00:00:00

abstract：:Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established conce...

journal_title：Statistical applications in genetics and molecular biology

authors： Dazard JE,Ishwaran H,Mehlotra R,Weinberg A,Zimmerman P

更新日期：2018-02-17 00:00:00

abstract：:There has been increasing interest in predicting patients' survival after therapy by investigating gene expression microarray data. In the regression and classification models with high-dimensional genomic data, boosting has been successfully applied to build accurate predictive models and conduct variable selection s...

journal_title：Statistical applications in genetics and molecular biology

authors： Wang Z,Wang CY

更新日期：2010-01-01 00:00:00

abstract：:In the exploding field of gene expression techniques such as DNA microarrays, there are still few general probabilistic methods for analysis of variance. Linear models and ANOVA are heavily used tools in many other disciplines of scientific research. The usual F-statistic is unsatisfactory for microarray data, which e...

journal_title：Statistical applications in genetics and molecular biology

authors： Lönnstedt I,Rimini R,Nilsson P

更新日期：2005-01-01 00:00:00

abstract：:Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which...

journal_title：Statistical applications in genetics and molecular biology

authors： Kiihl SF,Martinez-Garrido MJ,Domingo-Relloso A,Bermudez J,Tellez-Plaza M

更新日期：2019-01-17 00:00:00

abstract：:Consider the standard multiple testing problem where many hypotheses are to be tested, each hypothesis is associated with a test statistic, and large test statistics provide evidence against the null hypotheses. One proposal to provide probabilistic control of Type-I errors is the use of procedures ensuring that the e...

journal_title：Statistical applications in genetics and molecular biology

authors： Rubin D,Dudoit S,van der Laan M

更新日期：2006-01-01 00:00:00

abstract：:Making sound proteomic inferences using ELISA microarray assay requires both an accurate prediction of protein concentration and a credible estimate of its error. We present a method using monotonic spline statistical models (MS), penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to pr...

journal_title：Statistical applications in genetics and molecular biology

authors： Daly DS,Anderson KK,White AM,Gonzalez RM,Varnum SM,Zangar RC

更新日期：2008-01-01 00:00:00

abstract：:The Dirichlet Process (DP) mixture model has become a popular choice for model-based clustering, largely because it allows the number of clusters to be inferred. The sequential updating and greedy search (SUGS) algorithm (Wang & Dunson, 2011) was proposed as a fast method for performing approximate Bayesian inference ...

journal_title：Statistical applications in genetics and molecular biology

authors： Crook OM,Gatto L,Kirk PDW

更新日期：2019-12-12 00:00:00

abstract：:High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite di...

journal_title：Statistical applications in genetics and molecular biology

authors： Schimek MG,Budinská E,Kugler KG,Švendová V,Ding J,Lin S

更新日期：2015-06-01 00:00:00

abstract：:We present an approach to association studies involving a dozen or so ;response' variables and a few hundred ;explanatory' variables which emphasizes transparency, simplicity, and protection against spurious results. The methods proposed are largely non-parametric, and they are systematically rounded-off by the Benjam...

journal_title：Statistical applications in genetics and molecular biology

authors： Ferreira JA,Berkhof J,Souverein O,Zwinderman K

更新日期：2009-01-01 00:00:00

abstract：:We present a weighted-LASSO method to infer the parameters of a first-order vector auto-regressive model that describes time course expression data generated by directed gene-to-gene regulation networks. These networks are assumed to own prior internal structures of connectivity which drive the inference method. This ...

journal_title：Statistical applications in genetics and molecular biology

authors： Charbonnier C,Chiquet J,Ambroise C

更新日期：2010-01-01 00:00:00

abstract：:In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to exp...

journal_title：Statistical applications in genetics and molecular biology

authors： Shieh AD,Hung YS

更新日期：2009-01-01 00:00:00

abstract：:With the increasing availability of experimental data on gene interactions, modeling of gene regulatory pathways has gained special attention. Gradient descent algorithms have been widely used for regression and classification applications. Unfortunately, results obtained after training a model by gradient descent are...

journal_title：Statistical applications in genetics and molecular biology

authors： Das M,Murthy CA,De RK

更新日期：2014-02-01 00:00:00

abstract：:We are concerned with statistical inference for 2 × C × K contingency tables in the context of genetic case-control association studies. Multivariate methods based on asymptotic Gaussianity of vectors of test statistics require information about the asymptotic correlation structure among these test statistics under th...

journal_title：Statistical applications in genetics and molecular biology

authors： Dickhaus T,Stange J,Demirhan H

更新日期：2015-11-01 00:00:00

abstract：:Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a com...

journal_title：Statistical applications in genetics and molecular biology

authors： Taylor SL,Leiserowitz GS,Kim K

更新日期：2013-12-01 00:00:00

abstract：:Several important syndromes are caused by deleterious germline mutations of individual genes. In both clinical and research applications it is useful to evaluate the probability that an individual carries an inherited genetic variant of these genes, and to predict the risk of disease for that individual, using informa...

journal_title：Statistical applications in genetics and molecular biology

authors： Chen S,Wang W,Broman KW,Katki HA,Parmigiani G

更新日期：2004-01-01 00:00:00