In drostlab/edgynode: Comparison of Gene Regulatory Networks

library(edgynode)
options(width = 750)
knitr::opts_chunk$set(
  comment = "#>",
  error = FALSE,
  tidy = FALSE)

Table of Contents

1. Why edgynode?
2. Installation
3. Performing an Example Workflow for edgynode analysis

Why edgynode?

With the maturation of (single-cell) sequencing technologies across modalities, the inference of gene regulatory networks (GRN) is increasingly feasible. Yet, we lack a simple and powerful statistical package to benchmark GRN inference outcomes.

The edgynode package imports inferred gene regulatory networks and performs network statistics and network simulation procedures to investigate the topology and structure of the GRN at hand.

Installation

# install edgynode from GitHub
devtools::install_github("drostlab/edgynode")

Performing an Example Workflow for edgynode analysis

Load small example with internal dataset

# library(edgynode)

# Benchmark GENIE3 inferred networks with raw, no_noise, and quantile_norm combinations
genie3_49_raw <- as.matrix(read.csv(
  system.file("data/network_raw_49_placenta_development.csv",
              package = "edgynode"), row.names = 1))

genie3_49_noNoiseCM_raw <- as.matrix(read.csv(
  system.file("data/network_noNoiseCM_raw_49_placenta_development.csv",
              package = "edgynode"), row.names = 1))

genie3_49_qnorm_no_noise_removed <- as.matrix(read.csv(
  system.file("data/network_qnorm_49_placenta_development.csv",
              package = "edgynode"), row.names = 1))

genie3_49_noNoiseCM_qnorm <- as.matrix(read.csv(
  system.file("data/network_noNoiseCM_qnorm_49_placenta_development.csv",
              package = "edgynode"), row.names = 1))

Check data properties

is_adjacency(genie3_49_noNoiseCM_qnorm)

is_adjacency(make_adjacency(genie3_49_noNoiseCM_qnorm))

Benchmark small example with internal dataset

# Run Benchmark using Hamming distance
benchmark_hamming <- 
  network_benchmark_noise_filtering(
    genie3_49_raw,
    genie3_49_noNoiseCM_raw,
    genie3_49_qnorm_no_noise_removed,
    genie3_49_noNoiseCM_qnorm,
    dist_type = "hamming",
    grn_tool = "GENIE3")

# visualise results
plot_network_benchmark_noise_filtering(
  benchmark_hamming,
  dist_type = "hamming", 
  title = "Network Inference Tool: GENIE3")

drostlab/edgynode documentation built on March 29, 2024, 10:36 a.m.