merge samples
Usage
summarise_variables(
object,
what = c("sum_intensity", "mean_intensity", "median_intensity"),
variable_id,
variable_index,
remain_variable_info_id,
remain_variable_info_index,
group_by,
...
)
summarize_variables(
object,
what = c("sum_intensity", "mean_intensity", "median_intensity"),
variable_id,
variable_index,
remain_variable_info_id,
remain_variable_info_index,
group_by,
...
)
# S3 method for class 'microbiome_dataset'
summarise_variables(
object,
what = c("sum_intensity", "mean_intensity", "median_intensity"),
variable_id,
variable_index,
remain_variable_info_id,
remain_variable_info_index,
group_by,
...
)Arguments
- object
microbiome_dataset
- what
which you want to use
- variable_id
variables should be merged
- variable_index
variables should be merged
- remain_variable_info_id
which variable information should be used.
- remain_variable_info_index
which variable information should be used.
- group_by
group all variables by column in variable_info
- ...
other params
Examples
data(global_patterns)
dim(global_patterns)
#> variables samples
#> 19216 26
global_patterns
#> --------------------
#> microbiomedataset version: 0.99.1
#> --------------------
#> 1.expression_data:[ 19216 x 26 data.frame]
#> 2.sample_info:[ 26 x 8 data.frame]
#> 3.variable_info:[ 19216 x 8 data.frame]
#> 4.sample_info_note:[ 8 x 2 data.frame]
#> 5.variable_info_note:[ 8 x 2 data.frame]
#> --------------------
#> Processing information (extract_process_info())
#> create_microbiome_dataset ----------
#> Package Function.used Time
#> 1 microbiomedataset create_microbiome_dataset() 2022-07-11 01:56:13
global_patterns <-
global_patterns %>%
activate_microbiome_dataset(what = "variable_info") %>%
dplyr::filter(!is.na(Genus))
object <-
global_patterns %>%
summarize_variables(what = "sum_intensity", group_by = "Genus")
dim(object)
#> variables samples
#> 983 26