Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/515-extractPCMScales.R

Generalized Scales-Based Descriptors derived by Principal Components Analysis

1 | ```
extrPCMScales(x, propmat, pc, lag, scale = TRUE, silent = TRUE)
``` |

`x` |
A character vector, as the input protein sequence. |

`propmat` |
A matrix containing the properties for the amino acids. Each row represent one amino acid type, each column represents one property. Note that the one-letter row names must be provided for we need them to seek the properties for each AA type. |

`pc` |
Integer. Use the first pc principal components as the scales. Must be no greater than the number of AA properties provided. |

`lag` |
The lag parameter. Must be less than the amino acids. |

`scale` |
Logical. Should we auto-scale the property matrix
( |

`silent` |
Logical. Whether we print the standard deviation,
proportion of variance and the cumulative proportion of
the selected principal components or not.
Default is |

This function calculates the generalized scales-based descriptors derived by Principal Components Analysis (PCA). Users could provide customized amino acid property matrices. This function implements the core computation procedure needed for the generalized scales-based descriptors derived by AA-Properties (AAindex) and generalized scales-based descriptors derived by 20+ classes of 2D and 3D molecular descriptors (Topological, WHIM, VHSE, etc.) in the protr package.

A length `lag * p^2`

named vector,
`p`

is the number of scales (principal components) selected.

Min-feng Zhu <wind2zhu@163.com>, Nan Xiao <http://r2s.name>

See `extrPCMDescScales`

for generalized
AA property based scales descriptors, and `extrPCMPropScales`

for (19 classes) AA descriptor based scales descriptors.

1 2 3 4 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.