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The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix
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Lee A Newberg
Veröffentlicht/Copyright:
1. Juni 2005
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 sequences related by a phylogenetic tree. Using these we find that approaches based upon sequence weights can perform very poorly in comparison to approaches based upon a theoretically optimal maximum-likelihood method in the inference of the parameters of a position-weight matrix. Specifically, we find that among a collection of primate sequences, even an optimal sequences-weights approach is only 51% as efficient as the maximum-likelihood approach in inferences of base frequency parameters.We also show how to employ the variance estimators to obtain a greedy ordering of species for sequencing. Application of this ordering for the weighted estimators to a primate collection yields a curve with a long plateau that is not observed with maximum-likelihood estimators. This plateau indicates that the use of weighted estimators on these data seriously limits the utility of obtaining the sequences of more than two or three additional species.
Keywords: Sequence Weights; Maximum Likelihood; Motifs; Phylogeny; Sequencing; Consensus Distribution; Position-Weight Matrices
Published Online: 2005-6-1
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Schlagwörter für diesen Artikel
Sequence Weights;
Maximum Likelihood;
Motifs;
Phylogeny;
Sequencing;
Consensus Distribution;
Position-Weight Matrices
Artikel in diesem Heft
- Article
- Estimating Motifs Under Order Restrictions
- Reproducible Research: A Bioinformatics Case Study
- Generalized Rank Tests for Replicated Microarray Data
- Stepwise Normalization of Two-Channel Spotted Microarrays
- Comparing Automatic and Manual Image Processing in FLARE Assay Analysis for Colon Carcinogenesis
- Pixel-level Signal Modelling with Spatial Correlation for Two-Colour Microarrays
- Empirical Bayes Microarray ANOVA and Grouping Cell Lines by Equal Expression Levels
- Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data.
- Early Diagnostic Marker Panel Determination for Microarray Based Clinical Studies
- Prediction of Missing Values in Microarray and Use of Mixed Models to Evaluate the Predictors
- Combined Association and Linkage Analysis for General Pedigrees and Genetic Models
- Incorporating Biological Information as a Prior in an Empirical Bayes Approach to Analyzing Microarray Data
- The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix
- A Simple Loglinear Model for Haplotype Effects in a Case-Control Study Involving Two Unphased Genotypes
- Extension of the SIMLA Package for Generating Pedigrees with Complex Inheritance Patterns: Environmental Covariates, Gene-Gene and Gene-Environment Interaction
- Error Distribution for Gene Expression Data
- A General Framework for Weighted Gene Co-Expression Network Analysis
- Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm
- Comparing Bacterial DNA Microarray Fingerprints
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- Hierarchical Inverse Gaussian Models and Multiple Testing: Application to Gene Expression Data
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- Fold-Change Estimation of Differentially Expressed Genes using Mixture Mixed-Model
- Test on the Structure of Biological Sequences via Chaos Game Representation
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- Weighted Analysis of Paired Microarray Experiments
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