Generate sPLS-DA input data (for mixomics)

Creates an object that can be used as input for the (s)PLS-DA functions from the mixOmics package. It contains the omics dataset as well as the samples group membership in a list.

Usage

get_input_splsda(mo_data, dataset_name, group, multilevel = NULL)

Arguments

mo_data

A MultiDataSet-class object.

dataset_name

Character, name of the dataset from mo_data to analyse.

group

Character, the column name in the samples information data-frame to use as samples group (use get_samples_metadata to view the samples information data-frame for a omics dataset).

multilevel

Character vector of length 1 or 3 to be used as information about repeated measurements. See Details. Default value is NULL (no repeated measurements).

Value

A list, in which the first element corresponds to the omics dataset, with samples as rows and features as columns, and the second element (named 'Y') is a named factor vector, giving for each sample its group. The name of the dataset to be analysed is stored in the dataset_name attribute of the returned object.

Details

multilevel argument: enables the multilevel option (see mixOmics site) to deal with repeated measurements. mixOmics::splsda() enables one- and two-factor decomposition. For one-factor decomposition, multilevel argument should be the name of the column in the samples metadata that gives the ID of the observation units (e.g. the ID of the subjects that were measured several times). The resulting design matrix (stored in the multilevel argument of the returned object) will be a data-frame with one column which gives the ID (as integer) of the observation units corresponding to each sample in the omics datasets. For two-factor decomposition, multilevel should be of length 3. The first value, similarly to the one-factor decomposition, should be the name of the column in the samples metadata that gives the ID of the observation units (e.g. the ID of the subjects that were measured several times). The second and third values should be the name of the columns in the samples metadata that give the two factors considered. The resulting design matrix (stored in the multilevel argument of the returned object) will be a data-frame with three columns: the first column gives the ID (as integer) of the observation units corresponding to each sample in the omics datasets; the second and third columns give the levels of the two factors.