Description Usage Arguments Value Examples

View source: R/BayesKnockdown.r

Calculates posterior probabilities for each gene in a set of experiments is differentially expressed between two sets of experimental conditions. More generally, it calculates posterior probabilities that each measured variable is different between two classes, incorporating prior probabilities potentially unique to each variable.

1 | ```
BayesKnockdown.diffExp(y1, y2, prior = 0.5, g = sqrt(ncol(y1) + ncol(y2)))
``` |

`y1` |
Condition 1 outcome matrix: |

`y2` |
Condition 2 outcome matrix: |

`prior` |
Prior probabilities for the outcome variables. Defaults to 0.5 for all variables. |

`g` |
The value to use for Zellner's |

A vector of `p`

posterior probabilities indicating
the probability that each outcome variable is different
between the two classes.

1 2 3 4 5 6 7 8 |

BayesKnockdown documentation built on Nov. 8, 2020, 5:48 p.m.

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