This function filters out certain classes or metabolites of the metabolites vector. If aggregated_data is not empty, metabolites and class will also be filtered here.
Arguments
- metalyzer_se
SummarizedExperiment
- drop_metabolites
A character vector defining metabolite classes or individual metabolites to be removed
- drop_NA_concentration
A boolean whether to drop metabolites which have any NAs in their concentration value
- drop_quant_status
A character, vector of characters or list of characters specifying which quantification status to remove. Metabolites with at least one quantification status of this vector will be removed.
- min_percent_valid
A numeric lower threshold between 0 and 1 (t less than or equal to x) to remove invalid metabolites that do not meet a given percentage of valid measurements per group (default per Metabolite).
- valid_status
A character vector that defines which quantification status is considered valid.
- per_group
A character vector of column names from meta_data that will be used to split each metabolite into groups. The threshold `min_percent_valid` will be applied for each group. The selected columns from meta_data will be added to aggregated_data.
- inplace
If FALSE, return a copy. Otherwise, do operation inplace and return None.
Examples
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())
#> Input checks passed. Proceeding with reading webidq file.
#>
#>
#> _____ ______ _______ _________ ________ ___ ___ ___ ________ _______ ________
#> |\ _ \ _ \|\ ___ \|\___ ___\\ __ \|\ \ |\ \ / /|\_____ \|\ ___ \ |\ __ \
#> \ \ \\\__\ \ \ \ __/\|___ \ \_\ \ \|\ \ \ \ \ \ \/ / /\|___/ /\ \ __/|\ \ \|\ \
#> \ \ \\|__| \ \ \ \_|/__ \ \ \ \ \ __ \ \ \ \ \ / / / / /\ \ \_|/_\ \ _ _\
#> \ \ \ \ \ \ \ \_|\ \ \ \ \ \ \ \ \ \ \ \____ \/ / / / /_/__\ \ \_|\ \ \ \\ \|
#> \ \__\ \ \__\ \_______\ \ \__\ \ \__\ \__\ \_______\__/ / / |\________\ \_______\ \__\\ _\
#> \|__| \|__|\|_______| \|__| \|__|\|__|\|_______|\____/ / \|_______|\|_______|\|__|\|__|
#> \|____|/
#>
#>
#> Info: Reading color code "FFCBD2D7" as "#CBD2D7"
#> Info: Reading color code "FFB9DE83" as "#B9DE83"
#> Info: Reading color code "FFB9DE83" as "#B9DE83"
#> Info: Reading color code "FFA28BA3" as "#A28BA3"
#> Info: Reading color code "FFA28BA3" as "#A28BA3"
#> Info: Reading color code "FFB2D1DC" as "#B2D1DC"
#> Info: Reading color code "FF7FB2C5" as "#7FB2C5"
#> Info: Reading color code "FFB2D1DC" as "#B2D1DC"
#> Info: Reading color code "FF7FB2C5" as "#7FB2C5"
#>
#> Measured concentration values:
#> ------------------------------
#> 0% 25% 50% 75% 100%
#> 0.000000 0.286299 1.289381 6.308854 12522.000000
#>
#> NAs: 762 (3.74%)
#>
#>
#> Measured quantification status:
#> -------------------------------
#> Valid: 15419 (75.66%)
#> LOQ: 983 (4.82%)
#> LOD: 3978 (19.52%)
#> NAs: 0 (0%)
#>
drop_metabolites <- c("C0", "C2", "C3", "Metabolism Indicators",
inplace = TRUE
)
metalyzer_se <- MetAlyzer::filter_metabolites(metalyzer_se, drop_metabolites)
#> Info: 3 metabolites were removed!