Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au
SNP datasets are high-dimensional, often with thousands to millions of SNPs and hundreds to thousand...
<p>Gene selection based on principal component analysis. A) variance explained by components 1–6 fro...
AbstractThe detection of genes that show similar profiles under different experimental conditions is...
acute exposure of human bronchial epithelial cells to whole cigarette smoke. As is customary Princip...
<p>The distribution of the gene expression values shows evident trends represented by the vectors as...
<p>Principal component analysis (PCA) based on trunk sprouts in natural sites (NH) and disturbed sit...
Microarrays are a widespread technology mostly used to explore expression profiles for thousand of g...
Circles represent young (7-weeks-old) plants while older (13-weeks-old) plants are represented by tr...
Biplots in Practice is a comprehensive introduction to one of the most useful and versatile methods ...
<p>Data is based on 16S rRNA gene sequences retrieved from clone libraries Karnico ‘heavy’ and Moden...
Microarray studies are used in molecular biology to explore patterns of expression of thousands of g...
There has been a significant advancement in the application of statistical tools in plant pathology ...
<p>Biplot of the first two components of principal components analysis conducted on stem and leaf tr...
none10siGene co-expression analysis has emerged in the past 5 years as a powerful tool for gene func...
none10siGene co-expression analysis has emerged in the past 5 years as a powerful tool for gene func...
SNP datasets are high-dimensional, often with thousands to millions of SNPs and hundreds to thousand...
<p>Gene selection based on principal component analysis. A) variance explained by components 1–6 fro...
AbstractThe detection of genes that show similar profiles under different experimental conditions is...
acute exposure of human bronchial epithelial cells to whole cigarette smoke. As is customary Princip...
<p>The distribution of the gene expression values shows evident trends represented by the vectors as...
<p>Principal component analysis (PCA) based on trunk sprouts in natural sites (NH) and disturbed sit...
Microarrays are a widespread technology mostly used to explore expression profiles for thousand of g...
Circles represent young (7-weeks-old) plants while older (13-weeks-old) plants are represented by tr...
Biplots in Practice is a comprehensive introduction to one of the most useful and versatile methods ...
<p>Data is based on 16S rRNA gene sequences retrieved from clone libraries Karnico ‘heavy’ and Moden...
Microarray studies are used in molecular biology to explore patterns of expression of thousands of g...
There has been a significant advancement in the application of statistical tools in plant pathology ...
<p>Biplot of the first two components of principal components analysis conducted on stem and leaf tr...
none10siGene co-expression analysis has emerged in the past 5 years as a powerful tool for gene func...
none10siGene co-expression analysis has emerged in the past 5 years as a powerful tool for gene func...
SNP datasets are high-dimensional, often with thousands to millions of SNPs and hundreds to thousand...
<p>Gene selection based on principal component analysis. A) variance explained by components 1–6 fro...
AbstractThe detection of genes that show similar profiles under different experimental conditions is...