Description Slots Details Methods Author(s) Examples

The `countData`

class is used to define summaries of count data
and establishing prior and posterior parameters on distributions
defined upon the count data.

Objects of these class contain the following components:

`data` : | Count data (matrix). |

`replicates` : | The replicate structure of the data. Stored as a factor, but can be given in any form. |

`groups` : | Group (model) structure to test on the data (list). |

`annotation` : | Annotation data for each count (data.frame). |

`priorType` : | Character string describing the type of prior
information available in slot `'priors'` . |

`priors` : | Prior parameter information. Calculated by the
functions described in `getPriors` . |

`posteriors` : | Estimated (log)-posterior likelihoods for each group
(matrix). Calculated by the functions described in `getLikelihoods` . |

`estProps` : | Estimated proportion of tags belonging to each
group (numeric). Calculated by the functions described in
`getLikelihoods` . |

`nullPosts` : | If calculated, the posterior likelihoods for the data having no true expression of any kind. |

`seglens` : | Lengths of segments containing the counts
described in `data` . A matrix, but may be initialised with a
vector, or ignored altogether. See Details. |

The `seglens`

slot describes, for each row of the `data`

object, the length of the 'segment' that contains the number of counts
described by that row. For example, if we are looking at the number of
hits matching genes, the `seglens`

object would consist of
transcript lengths. Exceptionally, we may want to use different segment
lengths for different samples and so the slot takes the form of a
matrix. If the matrix has only one column, it is duplicated for all
samples. Otherwise, it should have the same number of columns as the
'@data' slot. If the slot is the empty matrix, then it is assumed that
all segments have the same length.

The standard methods 'new', 'dim', '[', 'show', 'rbind' and 'c' have been defined for these classes. The methods 'groups', 'groups<-', 'replicates', 'replicates<-', 'libsizes' and 'libsizes<-' have also been defined in order to access and modify these slots, and their use is recommended. The method 'flatten' can be used to produce a data.frame object containing much of the basic data in a member of this class.

Thomas J. Hardcastle

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
#load test data
data(simData)
# Create a 'countData' object from test data.
replicates <- c("simA", "simA", "simA", "simA", "simA", "simB", "simB", "simB", "simB", "simB")
groups <- list(NDE = c(1,1,1,1,1,1,1,1,1,1), DE = c(1,1,1,1,1,2,2,2,2,2))
CD <- new("countData", data = simData, replicates = replicates, groups = groups)
#estimate library sizes for countData object
libsizes(CD) <- getLibsizes(CD)
CD[1:10,]
dim(CD)
``` |

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