Accounting for undetected compounds in statistical analyses of mass spectrometry 'omic studies.

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：: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：: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：: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：: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：: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：: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：: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：: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：: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：: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：:In cellular biology, node-and-edge graph or "network" data collection often uses bait-prey technologies such as co-immunoprecipitation (CoIP). Bait-prey technologies assay relationships or "interactions" between protein pairs, with CoIP specifically measuring protein complex co-membership. Analyses of CoIP data freque...

journal_title：Statistical applications in genetics and molecular biology

authors： Scholtens DM,Spencer BD

更新日期：2015-08-01 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：: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：: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

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：: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：: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：: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：:The ENCODE project has funded the generation of a diverse collection of methylation profiles using reduced representation bisulfite sequencing (RRBS) technology, enabling the analysis of epigenetic variation on a genomic scale at single-site resolution. A standard application of RRBS experiments is in the location of ...

journal_title：Statistical applications in genetics and molecular biology

authors： Lacey MR,Baribault C,Ehrlich M

更新日期：2013-12-01 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：: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 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：: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：: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：: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：: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：: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：:Polytomous phenotypes arise when a disease has multiple subtypes or when two dichotomous phenotypes are analyzed simultaneously. Few software programs offer the option to analyze such phenotypes in family studies, and none implements conditional polytomous logistic regression for within-family analysis robust to popul...

journal_title：Statistical applications in genetics and molecular biology

authors： Bureau A,Croteau J

更新日期：2017-03-01 00:00:00