calc_pvalues_percentile: Compute interaction p values for a single percentile value

In elisabettasciacca/DEGGs: Differentially Expressed Gene-Gene pairs

Compute interaction p values for a single percentile value

Description

Compute interaction p values for a single percentile value

Usage

calc_pvalues_percentile(
  normalised_counts,
  metadata,
  subgroup_variable,
  subgroups_length,
  subgroups_df_list,
  sig_var,
  percentile,
  combinations,
  regression_method = "rlm",
  edges,
  sig_edges_count
)

Arguments

normalised_counts	a data frame containing normalised counts from an high throughput sequencing experiment. Sample IDs must be in columns and gene/miRNA/TFs in rows. Objects of class matrix are not allowed.
metadata	a data frame of sample data with rownames matching the sample IDs in normalised_counts colnames
subgroup_variable	column name in metadata that contains the subgroup identifier for each sample in normalised_counts
subgroups_length	integer number indicating the number of subgroups
subgroups_df_list	list of subgroup data frames
sig_var	Inherited from generate_subnetworks. It can be q.value or p.value depending on how use_qvalues was set in the generate_subnetworks function (default FALSE).
percentile	a float number indicating the percentile to use.
combinations	data frame containing the subgroups combinations in rows
regression_method	whether to use robust linear modelling to obtain p value of the interactions. Options are 'rlm' (default) or 'lm'
edges	network of biological interactions in the form of a table of class data.frame with two columns: "from" and "to".
sig_edges_count	number of significant edges (p < 0.05)

Value

The list of float numbers of the significant pvalues for a specific percentile

elisabettasciacca/DEGGs documentation built on April 27, 2024, 12:51 a.m.