Views of a multidimensional dataset, ranked by their differentiation power, non-Shiny version

Description

findviews_to_compare_core detects views on which two arbitrary sets of tuples are well separated. It produces the same results as findviews_to_compare, but does not present them with a Shiny app.

Usage

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findviews_to_compare_core(group1, group2, data, view_size_max = NULL,
  clust_method = "complete")

Arguments

group1

Logical vector of size nrow(data), which describes the first group to compare. The value TRUE at position i indicates the the i-th row of data belongs to the group.

group2

Logical vector, which describes the second group to compare. The value TRUE at position i indicates the the i-th row of data belongs to the group.

data

Data frame or matrix to be processed

view_size_max

Maximum number of columns in the views. If set to NULL, findviews uses log2(ncol(data)), rounded upwards and capped at 5.

clust_method

Character describing a clustering method, used internally by hclust. Example values are "complete", "single" or "average".

Details

The function findviews_to_compare_core takes two groups of tuples as input, and detects views on which the statistical distribution of those two groups is different. See the documentation of findviews_to_compare for more details.

The difference between findviews_to_compare and findviews_to_compare_core is that the former presents its results with a Shiny app, while the latter simply outputs them as R stuctures.

Examples

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