siamcat {SIAMCAT} | R Documentation

## SIAMCAT constructor function

### Description

Function to construct an object of class siamcat-class

### Usage

    siamcat(..., feat=NULL, label=NULL, meta=NULL,
        phyloseq=NULL, validate=TRUE, verbose=3)

### Arguments

`...` | additional arguments
`feat` | feature information for SIAMCAT (see details)
`label` | label information for SIAMCAT (see details)
`meta` | (optional) metadata information for SIAMCAT (see details)
`phyloseq` | (optional) a phyloseq object for the creation of an SIAMCAT object (see details)
`validate` | boolean, should the newly constructed SIAMCAT object be validated? defaults to TRUE (we strongly recommend against setting this parameter to FALSE)
`verbose` | control output: `0` for no output at all, `1` for only information about progress and success, `2` for normal level of information and `3` for full debug information, defaults to `1`

### Details

Build siamcat-class objects from their components.

This functions creates a SIAMCAT object (see siamcat-class). In order to do so, the function needs

- `feat` the feature information for SIAMCAT, should be either a matrix, a data.frame, or a otu_table-class. The columns should correspond to the different samples (e.g. patients) and the rows the different features (e.g. taxa). Columns and rows should be named.

- `meta` metadata information for the different samples in the feature matrix. Metadata is optional for the SIAMCAT workflow. Should be either a data.frame (with the rownames corresponding to the sample names of the feature matrix) or an object of class sample_data-class

- `phyloseq` Alternatively to supplying both feat and meta, SIAMCAT can also work with a phyloseq object containing an otu_table and other optional slots (like sample_data for meta-variables).

Notice: do supply either the feature information as matrix/data.frame/otu_table (and optionally metadata) or a phyloseq object, but not both.

The label information for SIAMCAT can take several forms:

- metadata column: if there is metadata (either via meta or as sample_data in the phyloseq object), the label object can be created by taking the information in a specific metadata column. In order to do so, `label` should be the name of the column, and `case` should indicate which group(s) should be the positive group(s). A typical example could look like that:

  `siamcat <- siamcat(feat=feat.matrix, meta=metadata, label='DiseaseState', case='CRC')`

  for the construction of a label to predict CRC status (which is encoded in the column `"DiseaseState"` of the metadata). For more control (e.g. specific labels for plotting or specific control state), the label can also be created outside of the `siamcat` function using the create.label function.

- named vector: the label can also be supplied as named vector which encodes the label either as characters (e.g. "Healthy" and "Diseased"), as factor, or numerically (e.g. -1 and 1). The vector must be named with the names of samples (corresponding to the samples in features). Also here, the information about the positive group(s) is needed via the `case` parameter. Internally, the vector is given to the create.label function.

- label object: A label object can be created with the create.label function or by reading a dedicated label file with read.label.

### Value

A new siamcat-class object

### Examples

    # example with package data
    data("feat_crc_zeller", package="SIAMCAT")
    data("meta_crc_zeller", package="SIAMCAT")

    siamcat <- siamcat(feat=feat.crc.zeller,
        meta=meta.crc.zeller,
        label='Group',
        case='CRC')

[Package SIAMCAT version 1.4.0 Index]