Description Usage Arguments Value Examples

View source: R/differential_methylation.R

The function takes a beta value matrix with probes on the rows and samples on the columns. It also takes a sample information data frame (sample.data) and formula for testing. The function outputs a list of coefficient tables for each factor tested.

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`betas` |
beta values |

`sample.data` |
data frame for sample information, column names are predictor variables (e.g., sex, age, treatment, tumor/normal etc) and are referenced in formula. Rows are samples. |

`formula` |
formula |

`se.lb` |
lower bound to standard error of slope, lower this to get more difference of small effect size. |

`balanced` |
whether design is balanced or not. default to FALSE, when unbalanced will use Welch's method to estimate standard error. balance=TRUE is faster. |

`cf.test` |
factors to test (default to all factors in formula except intercept). Use "all" for all factors. |

cf - a list of coefficient tables for each factor

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