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  • Search: isPartOf:"Statistical Applications in Genetics and Molecular Biology"
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multiple testing 28 gene expression 21 microarray 15 microarrays 14 bootstrap 11 false discovery rate 11 classification 10 null distribution 10 variable selection 10 cross-validation 9 Type I error rate 8 asymptotic control 8 model selection 8 prediction 7 Adjusted p-value 6 empirical Bayes 6 Microarrays 5 censoring 5 consistency 5 differential expression 5 machine learning 5 maximum likelihood 5 meta-analysis 5 multiple comparisons 5 normalization 5 EM algorithm 4 FDR 4 Markov chain Monte Carlo 4 SNP 4 augmentation 4 case-control 4 clustering 4 cut-off 4 family-wise error rate 4 generalized family-wise error rate 4 genetics 4 hidden Markov model 4 loss-based estimation 4 mass spectrometry 4 microarray analysis 4
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Undetermined 775
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Article 775
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Laan, Mark van der 35 van der Laan Mark J. 19 Dudoit, Sandrine 12 Hubbard, Alan 10 Pollard, Katherine 9 Rongling, Wu 9 Sinisi, Sandra 8 Bickel David R. 7 Keles, Sunduz 7 R, Segal Mark 7 Sandrine, Dudoit 7 Birkner, Merrill 6 Derek, Gordon 6 Dirk, Husmeier 6 J, Finch Stephen 6 Joseph, Beyene 6 Segal, Mark 6 Hubbard Alan E. 5 Sunduz, Keles 5 Thomas, Lengauer 5 Tomasz, Burzykowski 5 Ziv, Shkedy 5 Beyene, Joseph 4 Bickel, David 4 Boulesteix, Anne-Laure 4 Brad, McNeney 4 Burzykowski, Tomasz 4 Chad, Haynes 4 Dan, Lin 4 Eisen, Michael 4 Hongyu, Zhao 4 Jinko, Graham 4 Paul, Joyce 4 Pollard Katherine S. 4 Polley, Eric 4 Shkedy, Ziv 4 Smith, Martyn 4 Sylvia, Richardson 4 Tibshirani Robert J. 4 Wu, Rongling 4
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Statistical Applications in Genetics and Molecular Biology 775
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RePEc 775
Showing 671 - 680 of 775
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Pseudo-likelihood for Non-reversible Nucleotide Substitution Models with Neighbour Dependent Rates
Christensen Ole F. - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-31
In the field of molecular evolution genome substitution models with neighbour dependent substitution rates have recently received much attention. It is well-known that substitution of nucleotides does not occur independently of neighbouring nucleotides, but there has been less focus on the...
Persistent link: https://www.econbiz.de/10008460170
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Dimension Reduction for Classification with Gene Expression Microarray Data
J, Dai Jian; Linh, Lieu; David, Rocke - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-21
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...
Persistent link: https://www.econbiz.de/10008460171
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Treatment of Uninformative Families in Mean Allele Sharing Tests for Linkage
Indranil, Mukhopadhyay; Eleanor, Feingold; Tao, Wang; … - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-8
Using affected sibling pairs, the mean allele sharing statistic tests for linkage by testing if the mean proportion of alleles that are identical-by-descent (IBD) is equal to a half. The behavior of some versions of the mean allele sharing test statistic depends on whether or not families that...
Persistent link: https://www.econbiz.de/10008460181
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Computing Asymptotic Power and Sample Size for Case-Control Genetic Association Studies in the Presence of Phenotype and/or Genotype Misclassification Errors
Fei, Ji; Yaning, Yang; Chad, Haynes; J, Finch Stephen; … - In: Statistical Applications in Genetics and Molecular Biology 4 (2006) 1, pp. 1-27
It is well established that phenotype and genotype misclassification errors reduce the power to detect genetic association. Resampling a subset of the data (e.g, double-sampling) of genotype and/or phenotype with a gold standard measurement is one method to address this issue. We derive the...
Persistent link: https://www.econbiz.de/10008460187
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A New Type of Stochastic Dependence Revealed in Gene Expression Data
Lev, Klebanov; Craig, Jordan; Andrei, Yakovlev - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-24
Modern methods of microarray data analysis are biased towards selecting those genes that display the most pronounced differential expression. The magnitude of differential expression does not necessarily indicate biological significance and other criteria are needed to supplement the information...
Persistent link: https://www.econbiz.de/10008460216
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Validation in Genomics: CpG Island Methylation Revisited
R, Segal Mark - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-19
In a recent article in PLoS Genetics, Bock et al., (2006) undertake an extensive computational epigenetics analysis of the ability of DNA sequence-derived features, capturing attributes such as tetramer frequencies, repeats and predicted structure, to predict the methylation status of CpG...
Persistent link: https://www.econbiz.de/10008460227
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A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting
Daniel, Rubin; Sandrine, Dudoit; Mark, van der Laan - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-20
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...
Persistent link: https://www.econbiz.de/10008460228
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Treating Expression Levels of Different Genes as a Sample in Microarray Data Analysis: Is it Worth a Risk?
Lev, Klebanov; Andrei, Yakovlev - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-11
One of the prevailing ideas in the literature on microarray data analysis is to pool the expression measures across genes and treat them as a sample drawn from some distribution. Several universal laws were proposed to analytically describe this distribution. This idea raises a number of...
Persistent link: https://www.econbiz.de/10008460230
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Bayesian Hierarchical Model for Correcting Signal Saturation in Microarrays Using Pixel Intensities
Rashi, Gupta; Petri, Auvinen; Andrew, Thomas; Elja, Arjas - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-20
Pixel saturation occurs when the pixel intensity exceeds the scanner upper threshold of detection and the recorded pixel intensity is then truncated at the threshold. Truncation of the pixel intensity causes the estimates of gene expression (i.e., intensity) to be biased. Microarray experiments...
Persistent link: https://www.econbiz.de/10008460232
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A New Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity
Daniel, Dalevi; Devdatt, Dubhashi; Malte, Hermansson - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-26
Recently Peres and Shields discovered a new method for estimating the order of a stationary fixed order Markov chain. They showed that the estimator is consistent by proving a threshold result. While this threshold is valid asymptotically in the limit, it is not very useful for DNA sequence...
Persistent link: https://www.econbiz.de/10008460256
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