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

View source: R/estimateCommonDisp.R

Maximizes the negative binomial conditional common likelihood to estimate a common dispersion value across all genes.

1 2 3 4 5 | ```
## S3 method for class 'DGEList'
estimateCommonDisp(y, tol=1e-06, rowsum.filter=5, verbose=FALSE, ...)
## Default S3 method:
estimateCommonDisp(y, group=NULL, lib.size=NULL, tol=1e-06,
rowsum.filter=5, verbose=FALSE, ...)
``` |

`y` |
matrix of counts or a |

`tol` |
the desired accuracy, passed to |

`rowsum.filter` |
genes with total count (across all samples) below this value will be filtered out before estimating the dispersion. |

`verbose` |
logical, if |

`group` |
vector or factor giving the experimental group/condition for each library. |

`lib.size` |
numeric vector giving the total count (sequence depth) for each library. |

`...` |
other arguments that are not currently used. |

Implements the conditional maximum likelihood (CML) method proposed by Robinson and Smyth (2008) for estimating a common dispersion parameter. This method proves to be accurate and nearly unbiased even for small counts and small numbers of replicates.

The CML method involves computing a matrix of quantile-quantile normalized counts, called pseudo-counts. The pseudo-counts are adjusted in such a way that the library sizes are equal for all samples, while preserving differences between groups and variability within each group. The pseudo-counts are included in the output of the function, but are intended mainly for internal edgeR use.

`estimateCommonDisp.DGEList`

adds the following components to the input `DGEList`

object:

`common.dispersion` |
estimate of the common dispersion. |

`pseudo.counts` |
numeric matrix of pseudo-counts. |

`pseudo.lib.size` |
the common library size to which the pseudo-counts have been adjusted. |

`AveLogCPM` |
numeric vector giving log2(AveCPM) for each row of |

`estimateCommonDisp.default`

returns a numeric scalar of the common dispersion estimate.

Mark Robinson, Davis McCarthy, Gordon Smyth

Robinson MD and Smyth GK (2008).
Small-sample estimation of negative binomial dispersion, with applications to SAGE data.
*Biostatistics*, 9, 321-332.
http://biostatistics.oxfordjournals.org/content/9/2/321

`equalizeLibSizes`

,
`estimateTrendedDisp`

,
`estimateTagwiseDisp`

1 2 3 4 |

```
Loading required package: limma
Disp = 0.21178 , BCV = 0.4602
```

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