cogeqc

Workflows

Standard Workflow

Assess genome assembly and annotation quality by comparing custom statistics against NCBI genomes and evaluating gene space completeness with BUSCO.

library(cogeqc)

# 1. Retrieve and compare genome assembly statistics
maize_stats <- get_genome_stats(taxon = "Zea mays")
my_stats <- data.frame(
    accession = "my_lovely_maize",
    sequence_length = 2.4 * 1e9,
    gene_count_total = 50000,
    CC_ratio = 2
)
comparison <- compare_genome_stats(ncbi_stats = maize_stats, user_stats = my_stats)
plot_genome_stats(ncbi_stats = maize_stats, user_stats = my_stats)

# 2. Read and plot BUSCO summary statistics
output_dir <- system.file("extdata", package = "cogeqc")
busco_summary <- read_busco(output_dir)
plot_busco(busco_summary)

Input: Custom genome assembly statistics and BUSCO output directories; Output: Quality control comparison tables and summary visualization plots.

When to Use

• Assessing genome assembly and annotation quality by comparing custom statistics against NCBI genomes using get_genome_stats, compare_genome_stats, and plot_genome_stats.
• Assessing gene space completeness using BUSCO via run_busco, read_busco, and plot_busco.
• Assessing orthogroup inference (e.g., from OrthoFinder or OrthoMCL) using a protein domain-based approach with read_orthogroups and assess_orthogroups.

When NOT to Use

• For performing the actual genome assembly, gene annotation, or orthogroup clustering itself. Use external tools like Flye, Liftoff, or OrthoFinder, then use cogeqc for downstream quality control.