quality control pipeline for a simplified data.frame.

This function will run QC steps on a simplified data.frame.

Usage

QC_pipeline_df(
  object,
  filter_column_constant = TRUE,
  filter_column_missing_rate_threshold = 0.5,
  filter_row_missing_rate_threshold = NULL,
  replace_outlier_method = "winsorize",
  nSD = 5,
  impute_method = "half-min",
  run_batch_norm = FALSE,
  run_transform = "scale",
  verbose = TRUE
)

Arguments

object

A data.frame object, first two columnns are ID and Batch.

filter_column_constant

A logical value, whether to filter columns (features) with a constant value.

filter_column_missing_rate_threshold

A numeric threshold to filter columns (features) below a missing rate, default: 0.5. Other values: 0.2, 0.8. If NULL, then skip this step.

filter_row_missing_rate_threshold

A numeric threshold to filter rows (samples) below a missing rate. Default: NULL, to skip this step. Other values: 0.5, 0.2, 0.8.

replace_outlier_method

Method to replace outlier value, see replace_outlier.

nSD

Define the N times of the SD as outliers.

impute_method

Imputation method, the default method is half the minimum value (`half-min`) of the metabolite. Currently support 'half-min', "median", "mean", "zero".

run_batch_norm

Whether run run_batch_norm (`batch_norm_df`)

run_transform

Specify the transform method (`transformation`), eg. "log", "pareto_scale", "scale", "inverse_rank_transform". A User defined method is also supported.

verbose

print log information.

Value

A Metabolite object after QC.