mmstats: Print basic statistics of metagenome data
In KasperSkytte/mmgenome2: Tools for extracting individual genomes from metagenomes

Description Usage Arguments Details Value Author(s) Examples

Calculates some basic statistics like the N50 length, minimum-, mean-, and maximum scaffold lengths, mean GC content, information about essential genes, and more...

1	mmstats(mm, original_data = NULL, print = TRUE)

`mm`	(required) A dataframe loaded with `mmload`.
`original_data`	If `mm` is a subset/extraction of another dataframe loaded with `mmload`, then provide here the original dataframe from which the extraction originates to compare the extraction to the original data, see examples. (Default: `NULL`)
`print`	(logical) Whether to print the calculated stats or not. (Default: `TRUE`)

The returned stats are calculated as follows:

Scaffolds: The number of different scaffolds in the assembly.
N50: The shortest sequence length at 50
Length.total: The total size of the assembly.
Length.max: The size of the largest scaffold in the assembly.
Length.mean: The average scaffold size in the assembly.
Length.min: The size of the smallest scaffold in the assembly.
weighted_GC_mean: The average GC content in the assembly, weighted by scaffold sizes.
cov_*: The average coverage of each coverage variable in mm, weighted by scaffold sizes. (Only columns starting with "cov_" will be shown)
Ess.genes.total: The total number of essential genes, if any have been loaded.
Ess.genes.unique: The number of unique essential genes, if any have been loaded.

A dataframe with the calculated stats is returned invisibly.

Kasper Skytte Andersen ksa@bio.aau.dk

Soren M. Karst smk@bio.aau.dk

Mads Albertsen MadsAlbertsen85@gmail.com

library(mmgenome2)
data(mmgenome2)
mmstats(mmgenome2)

# Compare an extraction with the original data from which the extraction originates:
selection <- data.frame(
  cov_C13.11.25 = c(7.2, 16.2, 25.2, 23.3, 10.1),
  cov_C14.01.09 = c(47, 77, 52.8, 29.5, 22.1)
)
mmgenome2_extraction <- mmextract(mmgenome2,
  selection = selection
)

mmstats(mmgenome2_extraction, original_data = mmgenome2)