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Step: Preprocessing

step_preprocess.Rd

Preprocess the experiment using glyclean::auto_clean(). This step can be omitted if the experiment is already preprocessed.

This step requires exp (experiment data).

Usage

step_preprocess(
  batch_col = "batch",
  normalize_to_try = NULL,
  impute_to_try = NULL,
  remove_preset = "discovery",
  batch_prop_threshold = 0.3,
  check_batch_confounding = TRUE,
  batch_confounding_threshold = 0.4,
  rep_col = NULL
)

Arguments

batch_col

Column name for batch information (for QC plots and batch effect handling).

normalize_to_try

Normalization methods to try during auto_clean.

impute_to_try

Imputation methods to try during auto_clean.

remove_preset

Preset for data removal: "discovery", "biomarker", or NULL.

batch_prop_threshold

Threshold for batch proportion filtering.

check_batch_confounding

Whether to check for batch confounding.

batch_confounding_threshold

Threshold for batch confounding detection.

rep_col

Column name for replicate information (for QC plots).

Value

A glysmith_step object.

Details

Data required:

  • exp: The experiment to preprocess

Data generated:

  • raw_exp: The raw experiment (previous exp, saved for reference)

This step is special in that it silently overwrites the exp data with the preprocessed experiment. This ensures that no matter if preprocessing is performed or not, the "active" experiment is always under the key exp. The previous exp is saved as raw_exp for reference.

See also

glyclean::auto_clean()

Examples

step_preprocess()
#> <step "step_preprocess()"> Preprocessing
step_preprocess(remove_preset = "discovery")
#> <step "step_preprocess(remove_preset = \"discovery\")"> Preprocessing