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

View source: R/515-extractPCMScalesGap.R

Scales-Based Descriptors derived by Principal Components Analysis (with Gap Support)

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

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

`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 scales-based descriptors derived by Principal Components Analysis (PCA), with gap support. Users could provide customized amino acid property matrices. This function implements the core computation procedure needed for the scales-based descriptors derived by AA-Properties (AAindex) and scales-based descriptors derived by 20+ classes of 2D and 3D molecular descriptors (Topological, WHIM, VHSE, etc.) in the BioMedR 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://nanx.me>

See `extrProtFPGap`

for amino acid property based
scales descriptors (protein fingerprint) with gap support.

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