BayesMendel: an R environment for Mendelian risk prediction.

abstract：:We evaluate variable selection by multiple tests controlling the false discovery rate (FDR) to build a linear score for prediction of clinical outcome in high-dimensional data. Quality of prediction is assessed by the receiver operating characteristic curve (ROC) for prediction in independent patients. Thus we try to ...

journal_title：Statistical applications in genetics and molecular biology

authors： Graf AC,Bauer P

更新日期：2009-01-01 00:00:00

abstract：:The objective of the present paper is to develop a truly functional Bayesian method specifically designed for time series microarray data. The method allows one to identify differentially expressed genes in a time-course microarray experiment, to rank them and to estimate their expression profiles. Each gene expressio...

journal_title：Statistical applications in genetics and molecular biology

authors： Angelini C,De Canditiis D,Mutarelli M,Pensky M

更新日期：2007-01-01 00:00:00

abstract：:Output from analysis of a high-throughput 'omics' experiment very often is a ranked list. One commonly encountered example is a ranked list of differentially expressed genes from a gene expression experiment, with a length of many hundreds of genes. There are numerous situations where interest is in the comparison of ...

journal_title：Statistical applications in genetics and molecular biology

authors： Donald MR,Wilson SR

更新日期：2017-03-01 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：:Gametic models for fitting breeding values at QTL as random effects in outbred populations have become popular because they require few assumptions about the number and distribution of QTL alleles segregating. The covariance matrix of the gametic effects has an inverse that is sparse and can be constructed rapidly by ...

journal_title：Statistical applications in genetics and molecular biology

authors： Thallman RM,Hanford KJ,Kachman SD,Van Vleck LD

更新日期：2004-01-01 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：:We present a Bayesian hierarchical model for detecting differentially expressed genes using a mixture prior on the parameters representing differential effects. We formulate an easily interpretable 3-component mixture to classify genes as over-expressed, under-expressed and non-differentially expressed, and model gene...

journal_title：Statistical applications in genetics and molecular biology

authors： Lewin A,Bochkina N,Richardson S

更新日期：2007-01-01 00:00:00

abstract：:Certain residues have no known function yet are co-conserved across distantly related protein families and diverse organisms, suggesting that they perform critical roles associated with as-yet-unidentified molecular properties and mechanisms. This raises the question of how to obtain additional clues regarding these m...

journal_title：Statistical applications in genetics and molecular biology

authors： Neuwald AF

更新日期：2011-01-01 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：: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：: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：: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：:Multi-color optical mapping is a new technique being developed to obtain detailed physical maps (indicating relative positions of various recognition sites) of DNA molecules. We consider a study design in which the data consist of noisy observations of multiple copies of a DNA molecule marked with colors at recognitio...

journal_title：Statistical applications in genetics and molecular biology

authors： Tong L,Mets L,McPeek MS

更新日期：2007-01-01 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 problem of finding periodically expressed genes from time course microarray experiments is at the center of numerous efforts to identify the molecular components of biological clocks. We present a new approach to this problem based on the cyclohedron test, which is a rank test inspired by recent advances in algebr...

journal_title：Statistical applications in genetics and molecular biology

authors： Morton J,Pachter L,Shiu A,Sturmfels B

更新日期：2007-01-01 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：:Gene microarray technology is often used to compare the expression of thousand of genes in two different cell lines. Typically, one does not expect measurable changes in transcription amounts for a large number of genes; furthermore, the noise level of array experiments is rather high in relation to the available numb...

journal_title：Statistical applications in genetics and molecular biology

authors： Erickson S,Sabatti C

更新日期：2005-01-01 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：:Many gene- and pathway-based association tests have been proposed in the literature. Among them, the SKAT is widely used, especially for rare variants association studies. In this paper, we investigate the connection between SKAT and a principal component analysis. This investigation leads to a procedure that encompas...

journal_title：Statistical applications in genetics and molecular biology

authors： Chen Z,Han S,Wang K

更新日期：2017-07-26 00:00:00

abstract：:Longitudinal genomics data and survival outcome are common in biomedical studies, where the genomics data are often of high dimension. It is of great interest to select informative longitudinal biomarkers (e.g. genes) related to the survival outcome. In this paper, we develop a computationally efficient tool, LCox, fo...

journal_title：Statistical applications in genetics and molecular biology

authors： Sun J,Herazo-Maya JD,Wang JL,Kaminski N,Zhao H

更新日期：2019-02-13 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：: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：:Approaches based upon sequence weights, to construct a position weight matrix of nucleotides from aligned inputs, are popular but little effort has been expended to measure their quality. We derive optimal sequence weights that minimize the sum of the variances of the estimators of base frequency parameters for sequen...

journal_title：Statistical applications in genetics and molecular biology

authors： Newberg LA,McCue LA,Lawrence CE

更新日期：2005-01-01 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：:We develop an approach for microarray differential expression analysis, i.e. identifying genes whose expression levels differ between two or more groups. Current approaches to inference rely either on full parametric assumptions or on permutation-based techniques for sampling under the null distribution. In some situa...

journal_title：Statistical applications in genetics and molecular biology

authors： Rossell D,Guerra R,Scott C

更新日期：2008-01-01 00:00:00

abstract：:In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. However, these methods such as Approximate Bayesian Computation (ABC...

journal_title：Statistical applications in genetics and molecular biology

authors： Bertl J,Ewing G,Kosiol C,Futschik A

更新日期：2017-11-27 00:00:00

abstract：:Combining correlated p-values from multiple hypothesis testing is a most frequently used method for integrating information in genetic and genomic data analysis. However, most existing methods for combining independent p-values from individual component problems into a single unified p-value are unsuitable for the cor...

journal_title：Statistical applications in genetics and molecular biology

authors： Chien LC

更新日期：2020-11-06 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：: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