Description Usage Arguments Author(s) Examples

This function plots values based upon a model trained by `opls`

.

1 2 3 4 5 6 7 | ```
## S4 method for signature 'opls,ANY'
plot(x, y, typeVc = c("correlation", "outlier",
"overview", "permutation", "predict-train", "predict-test", "summary",
"x-loading", "x-score", "x-variance", "xy-score", "xy-weight")[7],
parAsColFcVn = NA, parCexN = 0.8, parCompVi = c(1, 2),
parDevNewL = TRUE, parEllipsesL = NA, parLabVc = NA, parTitleL = TRUE,
file.pdfC = NULL, .sinkC = NULL, ...)
``` |

`x` |
An S4 object of class |

`y` |
Currently not used. |

`typeVc` |
Character vector: the following plots are available: 'correlation': Variable correlations with the components, 'outlier': Observation diagnostics (score and orthogonal distances), 'overview': Model overview showing R2Ycum and Q2cum (or 'Variance explained' for PCA), 'permutation': Scatterplot of R2Y and Q2Y actual and simulated models after random permutation of response values; 'predict-train' and 'predict-test': Predicted vs Actual Y for reference and test sets (only if Y has a single column), 'summary' [default]: 4-plot summary showing permutation, overview, outlier, and x-score together, 'x-variance': Spread of raw variables corresp. with min, median, and max variances, 'x-loading': X-loadings (the 6 of variables most contributing to loadings are colored in red to facilitate interpretation), 'x-score': X-Scores, 'xy-score': XY-Scores, 'xy-weight': XY-Weights |

`parAsColFcVn` |
Optional factor character or numeric vector to be converted into colors for the score plot; default is NA [ie colors will be converted from 'y' in case of (O)PLS(-DA) or will be 'black' for PCA] |

`parCexN` |
Numeric: amount by which plotting text should be magnified relative to the default |

`parCompVi` |
Integer vector of length 2: indices of the two components to be displayed on the score plot (first two components by default) |

`parDevNewL` |
Should the graphics be displayed in a new window [default]; If FALSE, parLayL must be set to FALSE also |

`parEllipsesL` |
Should the Mahalanobis ellipses be drawn? If 'NA' [default], ellipses are drawn when either a character parAsColVcn is provided (PCA case), or when 'y' is a character factor ((O)PLS-DA cases). |

`parLabVc` |
Optional character vector for the labels of observations on the plot; default is NA [ie row names of 'x', if available, or indices of 'x', otherwise, will be used] |

`parTitleL` |
Should the titles of the plots be printed on the graphics (default = TRUE); It may be convenient to set this argument to FALSE when the user wishes to add specific titles a posteriori |

`file.pdfC` |
Figure filename (e.g. in case of batch mode) ending with '.pdf'; for multiple graphics, set parLayL to TRUE; default is NULL (no saving; displaying instead) |

`.sinkC` |
Character: Name of the file for R output diversion [default = NULL: no diversion]; Diversion of messages is required for the integration into Galaxy |

`...` |
Currently not used. |

Etienne Thevenot, [email protected]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
data(sacurine)
attach(sacurine)
for(typeC in c("correlation", "outlier", "overview",
"permutation", "predict-train","predict-test",
"summary", "x-loading", "x-score", "x-variance",
"xy-score", "xy-weight")) {
print(typeC)
if(grepl("predict", typeC))
subset <- "odd"
else
subset <- NULL
opLs <- opls(dataMatrix, sampleMetadata[, "gender"],
predI = ifelse(typeC != "xy-weight", 1, 2),
orthoI = ifelse(typeC != "xy-weight", 1, 0),
permI = ifelse(typeC == "permutation", 10, 0),
subset = subset,
printL = FALSE, plotL = FALSE)
plot(opLs, typeVc = typeC)
}
detach(sacurine)
``` |

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