Description Usage Arguments Value

Pearson correlation distance for continuous data: d = (1- cor(x_i, x_j))/2 where cor(x_i, x_j) is the correlation between vector x_i and vector x_j.

1 2 |

`X` |
A data matrix, e.g. gene expression |

`method` |
a character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated. |

`scale` |
A boolean indicating whether to normalize the columns (samples) of the data to the even sum. |

`base` |
A numeric value for the shared column sum, if scale is TRUE. |

`log_trans` |
A boolean indicating whether to log transform the data prio to distance computation (log(X + 1)). Default is FALSE. |

`log_base` |
A number indicating base for log transformation. Default is 10. |

A dissimilarity matrix, D.

nlhuong/buds documentation built on May 17, 2019, 3:13 a.m.

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.