Retrieve summary statistics for a genome assembly file — summary_genome • biomartr
Description: A summary statistics of specific genome features is generated. These statistics are useful to assess the genome quality of retrieved genome assemblies when performing comparative genomics tasks. This way, users can assess whether or not patterns found based on genome comparisons aren't just a technical artifact of differences in genome assembly quality.

# Retrieve summary statistics for a genome assembly file

Source: `R/summary_genome.R`
`summary_genome.Rd`

A summary statistics of specific genome features is generated. These statistics are useful to assess the genome quality of retrieved genome assemblies when performing comparative genomics tasks. This way, users can assess whether or not patterns found based on genome comparisons aren't just a technical artifact of differences in genome assembly quality.

    summary_genome(file, organism)

## Arguments

file

  file path to a genome assembly file in `fasta` format.

organism

  character string specifying the organism at hand.

## Details

The summary statistics include:

- `genome_size_mbp`: Genome size in mega base pairs

- `n50_mbp`: The N50 contig size of the genome assembly in mega base pairs

- `n_seqs`: The number of chromosomes/scaffolds/contigs of the genome assembly file

- `n_nnn`: The absolute number of NNNs (over all chromosomes or scaffolds or contigs) in the genome assembly file

- `rel_nnn`: The percentage (relative frequency) of NNNs (over all chromosomes or scaffolds or contigs) compared to the total number of nucleotides in the genome assembly file

- `genome_entropy`: The `Shannon Entropy` of the genome assembly file (median entropy over all individual chromosome entropies)

- `n_gc`: The total number of GCs (over all chromosomes or scaffolds or contigs) in the genome assembly file

- `rel_gc`: The (relative frequency) of GCs (over all chromosomes or scaffolds or contigs) compared to the total number of nucleotides in the genome assembly file

## See also

`summary_cds`, `getCollection`, `getGenome`, `read_genome`

## Author

Hajk-Georg Drost

## Examples

    if (FALSE) {
    # retrieve genome from NCBI RefSeq
    Sc <- biomartr::getGenome(db = "refseq", organism = "Saccharomyces cerevisiae")
    # compute genome assembly summary statistics
    Sc_genome_summary <- summary_genome(file = Sc, organism = "Saccharomyces cerevisiae")
    # look at results
    Sc_genome_summary
    }