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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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Undetermined 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 681 - 690 of 775
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Quantile-Function Based Null Distribution in Resampling Based Multiple Testing
van der Laan Mark J.; Hubbard Alan E. - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-30
Simultaneously testing a collection of null hypotheses about a data generating distribution based on a sample of independent and identically distributed observations is a fundamental and important statistical problem involving many applications. Methods based on marginal null distributions...
Persistent link: https://www.econbiz.de/10008460263
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Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data
Birkner Merrill D.; Hubbard Alan E.; van der Laan Mark J.; … - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-24
A new data filtering method for SELDI-TOF MS proteomic spectra data is described. We examined technical repeats (2 per subject) of intensity versus m/z (mass/charge) of bone marrow cell lysate for two groups of childhood leukemia patients: acute myeloid leukemia (AML) and acute lymphoblastic...
Persistent link: https://www.econbiz.de/10008460267
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Statistical Selection of Maintenance Genes for Normalization of Gene Expressions
Yifan, Huang; C, Hsu Jason; Mario, Peruggia; A, Scott … - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-18
Maintenance genes can be used for normalization in the comparison of gene expressions. Even though the absolute expression levels of maintenance genes may vary considerably among different tissues or cells, a set of maintenance genes may provide suitable normalization if their expression levels...
Persistent link: https://www.econbiz.de/10008460271
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A Heuristic Bayesian Method for Segmenting DNA Sequence Alignments and Detecting Evidence for Recombination and Gene Conversion
Anna, Kedzierska; Dirk, Husmeier - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-34
We propose a heuristic approach to the detection of evidence for recombination and gene conversion in multiple DNA sequence alignments. The proposed method consists of two stages. In the first stage, a sliding window is moved along the DNA sequence alignment, and phylogenetic trees are sampled...
Persistent link: https://www.econbiz.de/10008460279
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Using Complexity for the Estimation of Bayesian Networks
Peter, Salzman; Anthony, Almudevar - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-23
Statistical inference of graphical models has become an important tool in the reconstruction of biological networks of the type which model, for example, gene regulatory interactions. In particular, the construction of a score-based Bayesian posterior density over the space of models provides an...
Persistent link: https://www.econbiz.de/10008460304
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A Generalized Clustering Problem, with Application to DNA Microarrays
Ilana, Belitskaya-Levy - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-26
We think of cluster analysis as class discovery. That is, we assume that there is an unknown mapping called clustering structure that assigns a class label to each observation, and the goal of cluster analysis is to estimate this clustering structure, that is, to estimate the number of clusters...
Persistent link: https://www.econbiz.de/10008460322
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A Bayes Regression Approach to Array-CGH Data
Chi-Chung, Wen; Yuh-Jenn, Wu; Yung-Hsiang, Huang; … - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-22
This paper develops a Bayes regression model having change points for the analysis of array-CGH data by utilizing not only the underlying spatial structure of the genomic alterations but also the observation that the noise associated with the ratio of the fluorescence intensities is bigger when...
Persistent link: https://www.econbiz.de/10008460334
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A Two-Step Multiple Comparison Procedure for a Large Number of Tests and Multiple Treatments
Hongmei, Jiang; W, Doerge Rebecca - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-35
For situations where the number of tested hypotheses is increasingly large, the power to detect statistically significant multiple treatment effects decreases. As is the case with microarray technology, often researchers are interested in identifying differentially expressed genes for more than...
Persistent link: https://www.econbiz.de/10008460336
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Combining Results of Microarray Experiments: A Rank Aggregation Approach
P, DeConde Robert; Sarah, Hawley; Seth, Falcon; Nigel, Clegg - In: Statistical Applications in Genetics and Molecular Biology 5 (2006) 1, pp. 1-25
As technology for microarray analysis becomes widespread, it is becoming increasingly important to be able to compare and combine the results of experiments that explore the same scientific question. In this article, we present a rank-aggregation approach for combining results from several...
Persistent link: https://www.econbiz.de/10008460342
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Comparing Bacterial DNA Microarray Fingerprints
Alan, Willse; P, Chandler Darrell; Amanda, White; … - In: Statistical Applications in Genetics and Molecular Biology 4 (2005) 1, pp. 1-38
Epidemiologic and forensic investigations often require assays to detect subtle genetic differences between closely related microorganisms. Typically, gel electrophoresis is used to compare randomly amplified DNA fragments between microbial samples, where the patterns of DNA fragment sizes are...
Persistent link: https://www.econbiz.de/10008557869
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