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Empirical threshold values for quantitative trait mapping.
The detection of genes that control quantitative characters is a problem of great interest to the genetic mapping community. Methods for locating these quantitative trait loci (QTL) relative to mapsExpand
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R/qtl: QTL Mapping in Experimental Crosses
SUMMARY R/qtl is an extensible, interactive environment for mapping quantitative trait loci in experimental populations derived from inbred lines. Expand
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Permutation tests for multiple loci affecting a quantitative character.
The problem of detecting minor quantitative trait loci (QTL) responsible for genetic variation not explained by major QTL is of importance in the complete dissection of quantitative characters. TwoExpand
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Optimizing parental selection for genetic linkage maps.
Genetic linkage maps based on restriction fragment length polymorphisms are useful for many purposes; however, different populations are required to fulfill different objectives. Clones from theExpand
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Analysis of Variance for Gene Expression Microarray Data
We demonstrate that ANOVA methods can be used to normalize microarray data and provide estimates of changes in gene expression that are corrected for potential confounding effects. Expand
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Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors
BackgroundAlthough numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address thisExpand
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Statistical tests for differential expression in cDNA microarray experiments
Extracting biological information from microarray data requires appropriate statistical methods. The simplest statistical method for detecting differential expression is the t test, which can be usedExpand
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A Hidden Markov Model approach to variation among sites in rate of evolution.
The method of Hidden Markov Models is used to allow for unequal and unknown evolutionary rates at different sites in molecular sequences. Rates of evolution at different sites are assumed to be drawnExpand
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Fundamentals of experimental design for cDNA microarrays
Microarray technology is now widely available and is being applied to address increasingly complex scientific questions. Consequently, there is a greater demand for statistical assessment of theExpand
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Improved statistical tests for differential gene expression by shrinking variance components estimates.
Combining information across genes in the statistical analysis of microarray data is desirable because of the relatively small number of data points obtained for each individual gene. Here we developExpand
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