calculate_method: Calculate diversity values for a matrix of transcripts.
In esebesty/SplicingFactory: Splicing Diversity Analysis for Transcriptome Data

Description Usage Arguments Details Value

Calculate diversity values for a matrix of transcripts.

1	calculate_method(x, genes, method, norm = TRUE, verbose = FALSE)

`x`	An input `matrix`, or `data.frame` containing transcript-level expression values.
`genes`	Character vector with equal length to the number of rows of the input dataset with transcript-level expression values. The values in `x` are grouped into genes based on this vector.
`method`	Method to use for splicing diversity calculation, including naive entropy (`naive`), Laplace entropy (`laplace`), Gini index (`gini`), Simpson index (`simpson`) and inverse Simpson index (`invsimpson`). The default method is Laplace entropy.
`norm`	If `TRUE`, the entropy values are normalized to the number of transcripts for each gene. The normalized entropy values are always between 0 and 1. If `FALSE`, genes cannot be compared to each other, due to possibly different maximum entropy values.
`verbose`	If `TRUE`, the function will print additional diagnostic messages, besides the warnings and errors.

The function calculates diversity values on a matrix of transcript-level expression values, aggregated by the genes defined in the genes parameter.

Gene-level splicing diversity values in a data.frame, where each row belongs to a gene and each column belongs to a sample from the data, in addition to the first column, containing gene names, given in the 'genes' parameter.

esebesty/SplicingFactory documentation built on Feb. 27, 2022, 12:08 a.m.