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

Given a linear model fit at the exon level, test for differences in exon retention between experimental conditions.

1 | ```
diffSplice(fit, geneid, exonid=NULL, robust=FALSE, verbose=TRUE)
``` |

`fit` |
an |

`geneid` |
gene identifiers. Either a vector of length |

`exonid` |
exon identifiers. Either a vector of length |

`robust` |
logical, should the estimation of the empirical Bayes prior parameters be robustified against outlier sample variances? |

`verbose` |
logical, if |

This function tests for differential exon usage for each gene and for each column of `fit`

.

Testing for differential exon usage is equivalent to testing whether the log-fold-changes in the `fit`

differ between exons for the same gene.
Two different tests are provided.
The first is an F-test for differences between the log-fold-changes.
The other is a series of t-tests in which each exon is compared to the average of all other exons for the same gene.
The exon-level t-tests are converted into a genewise test by adjusting the p-values for the same gene by Simes method.
The minimum adjusted p-value is then used for each gene.

This function can be used on data from an exon microarray or can be used in conjunction with voom for exon-level RNA-seq counts.

An object of class `MArrayLM`

containing both exon level and gene level tests.
Results are sorted by geneid and by exonid within gene.

`coefficients` |
numeric matrix of coefficients of same dimensions as |

`t` |
numeric matrix of moderated t-statistics, of same dimensions as |

`p.value` |
numeric vector of p-values corresponding to the t-statistics |

`genes` |
data.frame of exon annotation |

`genecolname` |
character string giving the name of the column of |

`gene.F` |
numeric matrix of moderated F-statistics, one row for each gene. |

`gene.F.p.value` |
numeric matrix of p-values corresponding to |

`gene.simes.p.value` |
numeric matrix of Simes adjusted p-values, one row for each gene. |

`gene.genes` |
data.frame of gene annotation. |

Gordon Smyth and Charity Law

A summary of functions available in LIMMA for RNA-seq analysis is given in 11.RNAseq.

1 2 3 4 5 6 7 8 | ```
## Not run:
v <- voom(dge,design)
fit <- lmFit(v,design)
ex <- diffSplice(fit,geneid="EntrezID")
topSplice(ex)
plotSplice(ex)
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.