summariseLoci


    A `lociData' object with calculated values in the `@lociLikelihoods' slot.



    Should the expectation be calculated on a per replicate group basis,
    or the total number of loci identified in the dataset?


perReplicate


  Summarises the expected number of loci, either in toto or on a per
  replicate group basis.


mainip

High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.

Thomas J Hardcastle

segmentSeq

Methods for identifying small RNA loci from high-throughput
sequencing data

summariseLoci function

A `lociData' object with calculated values in the `@lociLikelihoods' slot.

Should the expectation be calculated on a per replicate group basis,
    or the total number of loci identified in the dataset?

Summarises the expected number of loci, either in toto or on a per
  replicate group basis.

summariseLoci: Summarise the expected number of loci in a `lociData' object.

Description

Usage

Arguments

Value