Stats

This section shows several examples of the many methods that can be used in bioscience to perform statistical applications.

Suppose you have an object called dataset with your dataset loaded. To see how a data load is performed, please refer to the Load data section of this user guide.

In these cases, the pre-processed dataset will be found modified in the dataset.data attribute, while the originally loaded dataset will be found stored in the dataset.original attribute. This is because the user may wish to display or use the original dataset data for further validation or visualisation processes.

Correlation methods

The following examples show how to use correlation methods such as Kendall, Spearman, NMI, among others.

import bioscience as bs
resultsCorrelation = bs.kendall(dataset)
resultsCorrelation = bs.spearman(dataset)
resultsCorrelation = bs.nmi(dataset)

To understand the meaning of each attribute you can access the API reference.

Distance methods

The following examples show how to use distance methods such as Jaccard index, Manhattan, Euclidean, among others.

import bioscience as bs
resultsCorrelation = bs.jaccard(dataset)
resultsCorrelation = bs.manhattan(dataset)
resultsCorrelation = bs.euclidean(dataset)

To understand the meaning of each attribute you can access the API reference.