extract_intensity — extract_intensity • microbiomedataset

extract_intensity

extract_intensity(
  object,
  sample_wise = "sample_id",
  taxonomic_rank = c("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Species"),
  data_type = c("wider", "longer"),
  what = c("sum_intensity", "mean_intensity", "median_intensity"),
  na.rm = TRUE,
  relative = TRUE,
  ...
)

# S3 method for microbiome_dataset
extract_intensity(
  object,
  sample_wise = "sample_id",
  taxonomic_rank = c("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Species"),
  data_type = c("longer", "wider"),
  what = c("sum_intensity", "mean_intensity", "median_intensity"),
  na.rm = TRUE,
  relative = TRUE,
  ...
)

Arguments

object: microbiome_dataset
sample_wise: sample_wise, default is sample_id
taxonomic_rank: taxonomic_rank
data_type: if return_same_object is FALSE, the return data.frame
what: which you want to mutate
na.rm: na.rm
relative: relative intensity or not
...: other params

Value

microbiome_dataset

Examples

data("global_patterns", package = "microbiomedataset")

x <-
  extract_intensity(
    object = global_patterns,
    taxonomic_rank = "Genus",
    data_type = "longer",
    relative = TRUE
  )
head(x)
#>   sample_id         Genus        value
#> 1    AQC1cm          4-29 0.5340725502
#> 2    AQC1cm      4041AA30 0.0000000000
#> 3    AQC1cm           A17 0.8746237084
#> 4    AQC1cm   Abiotrophia 0.0000000000
#> 5    AQC1cm Acaryochloris 0.0052303079
#> 6    AQC1cm   Acetivibrio 0.0005811453
x <-
  extract_intensity(
    object = global_patterns,
    taxonomic_rank = "Genus",
    data_type = "wider",
    relative = FALSE,
    what = "sum_intensity"
  )
head(x[, 1:5])
#>               AQC1cm AQC4cm AQC7cm  CC1  CL3
#> 4-29             919   5586   8175    3    2
#> 4041AA30           0      4      0    0    0
#> A17             1505   1046   1003 4242 1061
#> Abiotrophia        0      0      0    0    0
#> Acaryochloris      9      0      3    0    0
#> Acetivibrio        1      5      3    0    0