Color data as interpreted in a color opponency framework. Raw color data are provided along with normalized response values and a color opponency score for each sampling location on the body. These scores are averaged within sampling areas and form the data used in PCA analysis
Principle component analysis (PCA) of all samples. Low-iron samples are shown in blue, high-iron in ...
Each color corresponds to a different batch. A = per batch normalization with no QCs, B = per batch ...
<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond t...
Color data as interpreted in a color opponency framework. Raw color data are provided along with nor...
<p>We used PCA to describe dewlap and ventral patch hue, chroma, and brightness as an independent co...
Color data as interpreted using MWS and LWS as independent values. Raw data are given along with ave...
<p>Colors denote extraction method: DNeasy (blue), PowerFecal (pink), CadorPathogen (purple), QIAmp ...
Font color inherits the arrow color (default). Font colors can be adjusted in the plots. Sizes of th...
Each column represents a vector of 7680 elements that were obtained from the calculation of 20 PCA, ...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Red, green and blue marker colors correspond to samples from Infiltrative, Superficial and Nodular B...
The figure shows the first two principal components after merging the acquired datasets. The samples...
Factor scores for PC1-20 for dorsal coloration per individual, per habitat (I: island, M:mainland), ...
<p>Note: Each colored point represents a sample. The first, second and third principal components ar...
<p>Samples are displayed in respect to the first three components and are colored with respect to di...
Principle component analysis (PCA) of all samples. Low-iron samples are shown in blue, high-iron in ...
Each color corresponds to a different batch. A = per batch normalization with no QCs, B = per batch ...
<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond t...
Color data as interpreted in a color opponency framework. Raw color data are provided along with nor...
<p>We used PCA to describe dewlap and ventral patch hue, chroma, and brightness as an independent co...
Color data as interpreted using MWS and LWS as independent values. Raw data are given along with ave...
<p>Colors denote extraction method: DNeasy (blue), PowerFecal (pink), CadorPathogen (purple), QIAmp ...
Font color inherits the arrow color (default). Font colors can be adjusted in the plots. Sizes of th...
Each column represents a vector of 7680 elements that were obtained from the calculation of 20 PCA, ...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Red, green and blue marker colors correspond to samples from Infiltrative, Superficial and Nodular B...
The figure shows the first two principal components after merging the acquired datasets. The samples...
Factor scores for PC1-20 for dorsal coloration per individual, per habitat (I: island, M:mainland), ...
<p>Note: Each colored point represents a sample. The first, second and third principal components ar...
<p>Samples are displayed in respect to the first three components and are colored with respect to di...
Principle component analysis (PCA) of all samples. Low-iron samples are shown in blue, high-iron in ...
Each color corresponds to a different batch. A = per batch normalization with no QCs, B = per batch ...
<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond t...
DOI
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