percentile_cor: Compute percentile correlations between a set of transcripts

In ConesaLab/acorde: Isoform co-usage networks from single-cell RNA-seq data

Compute percentile correlations between a set of transcripts

Description

This function summarizes expression for each cell type using percentiles and then calculates Pearson correlations between all possible transcript pairs in the data set. Internally, the function function calls percentile_expr to generate percentile-summarized expression, and then cor to compute Pearson correlation

Usage

percentile_cor(data, id_table, percentile_no = 10, isoform_col = NULL)

Arguments

data	A data.frame or tibble object including isoforms as rows and cells as columns. Isoform IDs can be included as row names (data.frame) or as an additional column (tibble).
id_table	A data frame including two columns named cell and cell_type, in which correspondence between cell ID and cell type should be provided. The number of rows should be equal to the total number of cell columns in data, and the order of the cell column should match column (i.e. cell) order in data.
percentile_no	Integer indicating the number of percentiles to generate for each of the cell types. Should always be higher than 4 (quantiles) and lower than 100 (percentiles). Defaults to 10.
isoform_col	When a tibble is provided in data, a character value indicating the name of the column in which isoform IDs are specified.

Value

A correlation matrix including one column-row pair per isoform included in data.

ConesaLab/acorde documentation built on Feb. 25, 2024, 4:16 a.m.