This is the development version of segmentSeq; for the stable release version, see segmentSeq.
Methods for identifying small RNA loci from high-throughput sequencing dataBioconductor version: Development (3.22)
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.
Author: Thomas J. Hardcastle [aut], Samuel Granjeaud [cre] ORCID: 0000-0001-9245-1535
Maintainer: Samuel Granjeaud <samuel.granjeaud at inserm.fr>
Citation (from within R, entercitation("segmentSeq")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("segmentSeq")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("segmentSeq")Follow Installation instructions to use this package in your R session.
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