predict_ffls_two_groups: predict_ffls_two_groups

In th789/fflmediation: Predict Feed Forward Loops Using Mediation Analysis

predict_ffls_two_groups

Description

function to predict FFLs unique to one of two biological groups

Usage

predict_ffls_two_groups(
  mirna_expr_g1,
  mrna_expr_g1,
  mirna_expr_g2,
  mrna_expr_g2,
  ffl_type = c("miRNA", "TF"),
  candidate_ffls,
  first_row = 1,
  last_row = nrow(candidate_ffls),
  num_bootstrap_samples = 1000,
  num_permutations = 1000,
  p_value_adjust_method = c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY",
    "fdr", "locfdr", "none"),
  seed = 12345,
  parallel = TRUE
)

Arguments

mirna_expr_g1	Group 1's miRNA expression data (dataframe: miRNAs x samples, see sample_mirna_expr_g1)
mrna_expr_g1	Group 1's mRNA expression data (dataframe: mRNAs x samples, see sample_mrna_expr_g1)
mirna_expr_g2	Group 2's miRNA expression data (dataframe: miRNAs x samples, see sample_mirna_expr_g2)
mrna_expr_g2	Group 2's miRNA expression data (dataframe: miRNAs x samples, see sample_mirna_expr_g2)
ffl_type	FFL type (character: "miRNA" or "TF")
candidate_ffls	candidate FFLs (dataframe: candidate FFLs x 10, see sample_candidate_ffls_mirna)
first_row	first row of candidate_ffls dataframe to include in analyses (integer: default = 1)
last_row	last row of candidate_ffls dataframe to include in analyses (integer: default = nrow(candidate_ffls))
num_bootstrap_samples	number of bootstrap samples (integer: default = 1000)
num_permutations	number of permutations (integer: default = 1000)
p_value_adjust_method	method to adjust p-values for multiple testing (character: "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "locfdr", or "none")
seed	random seed (integer: default = 12345)
parallel	whether to run analyses in parallel (boolean: default = TRUE)

Value

candidate FFLs with delta-P(FFL) values, p-values, and coefficient estimates (dataframe: number of candidate FFLs x 85 for miRNA-FFLs; number of candidate FFLs x 86 for TF-FFLs; see sample output)

th789/fflmediation documentation built on June 13, 2022, 1:02 p.m.