Print basic statistics of metagenome data

Source: R/mmstats.R

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

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

Arguments

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)

Value

A dataframe with the calculated stats is returned invisibly.

Details

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.

Author

Kasper Skytte Andersen ksa@bio.aau.dk

Soren M. Karst smk@bio.aau.dk

Mads Albertsen MadsAlbertsen85@gmail.com

Examples

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

#>                   General stats
#> Scaffolds             97 285   
#> N50                    5 291   
#> Length.total     331 908 376   
#> Length.max         1 446 979   
#> Length.mean            3 411.71
#> Length.min             1 000   
#> weighted_GC_mean          52.22
#> cov_C13.11.14              2.62
#> cov_C13.11.25             16.06
#> cov_C13.12.03              2.91
#> cov_C14.01.09             11.58
#> Ess.genes.total        7 138   
#> Ess.genes.unique         109   

# 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
)

#> 61 scaffolds (or 1.34% of the scaffolds in mm, weighted by length) remain after 97224 of 97285 scaffolds have been filtered.

mmstats(mmgenome2_extraction, original_data = mmgenome2)

#>                               General stats
#> Scaffolds                             61   
#> N50                              199 460   
#> Length.total                   4 452 901   
#> Length.max                       454 223   
#> Length.mean                       72 998.38
#> Length.min                         1 043   
#> weighted_GC_mean                      70.96
#> cov_C13.11.14 (% of original)          0.3 
#> cov_C13.11.25 (% of original)          1.11
#> cov_C13.12.03 (% of original)          3.19
#> cov_C14.01.09 (% of original)          4.49
#> Ess.genes.total                      109   
#> Ess.genes.unique                     105