regression | R Documentation |

Run regression models with adjusting for covariates. 'regression_each' is used for one outcome. In 'regression', several outcomes can be specified to run together.

regression( object, phenoData = NULL, model = NULL, outcome = NULL, covars = NULL, factors = NULL, feature_name = NULL, time = NULL, verbose = TRUE, ncpus = 1, p.adjust.method = "bonferroni", ... ) regression_each( object, phenoData = NULL, model = NULL, formula = NULL, outcome = NULL, covars = NULL, factors = NULL, feature_name = NULL, time = NULL, verbose = TRUE, ncpus = 1, p.adjust.method = "bonferroni", ... )

`object` |
A Metabolite object. |

`phenoData` |
A data.table with outcome and covariates. If 'phenoData' is NULL, '@sampleData' will be used. |

`model` |
Specify a regression model. See |

`outcome` |
Column name of the outcome variable. |

`covars` |
Column names of covariates. |

`factors` |
Variables to be treated as factor. |

`feature_name` |
A vector of selected metabolites to run. If both feature_name and random_select are NULL, will run regression for all features. |

`time` |
Column name of survival time, used in cox regression, see |

`verbose` |
Print log information. |

`ncpus` |
Number of CPUS for parallele job. |

`p.adjust.method` |
Adjust for P value method, see |

`...` |
Further arguments passed to regression model. |

`formula` |
A character or formula object to fit model (only used in 'regression_each') |

term estimate std.error statistic p.value n outcome p.value.adj.

data(df_plasma) fit_lm <- regression(object = df_plasma, phenoData = NULL, model = "lm", outcome = "BMI", covars = c("AGE", "GENDER", "ETHNICITY"), factors = "ETHNICITY")

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