Create a SplineOmics object — create_splineomics • SplineOmics

Creates a SplineOmics object containing variables that are commonly used across multiple functions in the package.

Usage

create_splineomics(
  data,
  meta,
  condition,
  rna_seq_data = NULL,
  annotation = NULL,
  report_info = NULL,
  meta_batch_column = NULL,
  meta_batch2_column = NULL,
  feature_name_columns = NULL,
  design = NULL,
  mode = NULL,
  spline_params = NULL,
  padjust_method = "BH"
)

Arguments

data: The actual omics data. In the case the rna_seq_data argument is used, still provide this argument. In that case, input the data matrix in here (for example the $E part of the voom object). Assign your feature names as row headers (otherwise, just numbers will be your feature names).
meta: Metadata associated with the omics data.
condition: A condition variable.
rna_seq_data: An object containing the preprocessed RNA-seq data, such as the output from `limma::voom` or a similar preprocessing pipeline. This argument is not controlled by any function of the `SplineOmics` package. Rather, in that regard it relies on the input control from the `limma::lmfit` function.
annotation: A dataframe with the feature descriptions of data (optional).
report_info: A list containing report information such as omics data type, data description, data collection date, analyst name, contact info, and project name (optional).
meta_batch_column: Column for meta batch information (optional).
meta_batch2_column: Column for secondary meta batch information (optional).
feature_name_columns: Character vector containing the column names of the annotation info that describe the features. This argument is used to specify in the HTML report how exactly the feature names displayed above each individual spline plot have been created. Use the same vector that was used to create the row headers for the data matrix!
design: A design matrix or similar object (optional).
mode: For the design formula, you must specify either 'isolated' or 'integrated'. Isolated means limma determines the results for each level using only the data from that level. Integrated means limma determines the results for all levels using the full dataset (from all levels).
spline_params: Parameters for spline functions (optional). Must contain the named elements spline_type, which must contain either the string "n" for natural cubic splines, or "b", for B-splines, the named element degree in the case of B-splines, that must contain only an integer, and the named element dof, specifying the degree of freedom, containing an integer and required both for natural and B-splines.
padjust_method: Method for p-value adjustment, one of "none", "BH", "BY", "holm", "bonferroni", "hochberg", or "hommel". Defaults to "BH" (Benjamini-Hochberg).

Value

A SplineOmics object.