Description Usage Arguments Value Author(s) References See Also Examples

Obtain significance results for quasi-likelihood model fits to RNA-seq expression count data using the methods detailed in Lund, Nettleton, McCarthy, and Smyth (2012).

1 2 | ```
QL.results(fit,Dispersion="Deviance",spline.df=NULL,Plot=TRUE)
``` |

`fit` |
The list returned by the function QL.fit |

`Dispersion` |
Must be one of "Deviance" or "Pearson", specifying which type of estimator should be used for estimating quasi-likelihood dispersion parameter. |

`spline.df` |
Optional. User may specify the degrees of freedom to use when fitting a cubic spline to log-scale(estimated dispersion) versus the log(average count). Default uses cross-validation in |

`Plot` |
logical. If TRUE, the estimated dispersion versus the average count are plotted on a log-scale with the corresponding cubic spline fit overlaid. |

list containing:

`"P.values"` |
list of matrices providing p-values for the QL, QLShrink and QLSpline methods, respectively. The i^th column of each element of |

`"Q.values"` |
list of matrices providing q-values for the QL, QLShrink and QLSpline methods, respectively. The i^th column of each element of |

`"F.stat"` |
list of matrices providing F-statistics for the QL, QLShrink and QLSpline methods, respectively. The i^th column of each element of |

`"m0"` |
matrix providing estimated number of true null hypotheses for each test(arranged by row) under each of the three methods(arranged by column). |

`"d0"` |
vector containing estimated additional denominator degrees of freedom gained from shrinking dispersion estimates in the QLShrink and QLSpline procedures, respectively. |

Steve Lund [email protected]

Lund, Nettleton, McCarthy and Smyth (2012) "Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates" *SAGMB*, **11**(5).

1 2 | ```
## see examples for QL.fit()
``` |

QuasiSeq documentation built on July 10, 2017, 1:05 a.m.

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