library(metaboprep)
# Somalogic data file path
filepath <- system.file("extdata", "somalogic_v1_example.adat", package = "metaboprep")
# read Somalogic data
somalogic_data <- read_somalogic(filepath)
# create the object (downsampled for speed)
m <- Metaboprep(data = somalogic_data$data[1:9, 1:100],
samples = somalogic_data$samples[1:9, ],
features = somalogic_data$features[1:100, ])
# run QC
m <- m |>
quality_control(source_layer = "input",
sample_missingness = 0.5,
feature_missingness = 0.3,
total_peak_area_sd = 5,
outlier_udist = 5,
outlier_treatment = "leave_be",
winsorize_quantile = 1.0,
tree_cut_height = 0.5,
pc_outlier_sd = 5,
sample_ids = NULL,
feature_ids = NULL)
#>
#> ── Starting Metabolite QC Process ──────────────────────────────────────────────
#> ℹ Validating input parameters
#> ✔ Validating input parameters [8ms]
#>
#> ℹ Sample & Feature Summary Statistics for raw data
#> ✔ Sample & Feature Summary Statistics for raw data [434ms]
#>
#> ℹ Copying input data to new 'qc' data layer
#> ✔ Copying input data to new 'qc' data layer [22ms]
#>
#> ℹ Assessing for extreme sample missingness >=80% - excluding 0 sample(s)
#> ✔ Assessing for extreme sample missingness >=80% - excluding 0 sample(s) [16ms]
#>
#> ℹ Assessing for extreme feature missingness >=80% - excluding 0 feature(s)
#> ✔ Assessing for extreme feature missingness >=80% - excluding 0 feature(s) [16m…
#>
#> ℹ Assessing for sample missingness at specified level of >=50% - excluding 0 sa…
#> ✔ Assessing for sample missingness at specified level of >=50% - excluding 0 sa…
#>
#> ℹ Assessing for feature missingness at specified level of >=30% - excluding 0 f…
#> ✔ Assessing for feature missingness at specified level of >=30% - excluding 0 f…
#>
#> ℹ Calculating total peak abundance outliers at +/- 5 Sdev - excluding 0 sample(…
#> ✔ Calculating total peak abundance outliers at +/- 5 Sdev - excluding 0 sample(…
#>
#> ℹ Running sample data PCA outlier analysis at +/- 5 Sdev
#> ✔ Running sample data PCA outlier analysis at +/- 5 Sdev [16ms]
#>
#> ℹ Sample PCA outlier analysis - re-identify feature independence and PC outlier…
#> [1] 8
#> [1] 9 9
#> ✔ Sample PCA outlier analysis - re-identify feature independence and PC outlier…
#>
#> ℹ Creating final QC dataset...
#> ✔ Creating final QC dataset... [392ms]
#>
#> ℹ Metabolite QC Process Completed
#> ✔ Metabolite QC Process Completed [14ms]
#>
