gpart

DOI: 10.18129/B9.bioc.gpart  

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.16 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see gpart.

Human genome partitioning of dense sequencing data by identifying haplotype blocks

Bioconductor version: 3.16

we provide a new SNP sequence partitioning method which partitions the whole SNP sequence based on not only LD block structures but also gene location information. The LD block construction for GPART is performed using Big-LD algorithm, with additional improvement from previous version reported in Kim et al.(2017). We also add a visualization tool to show the LD heatmap with the information of LD block boundaries and gene locations in the package.

Author: Sun Ah Kim [aut, cre, cph], Yun Joo Yoo [aut, cph]

Maintainer: Sun Ah Kim <sunnyeesl at gmail.com>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("gpart")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

PDF		Reference Manual

Details

biocViews	Clustering, Software
Version	1.16.0
In Bioconductor since	BioC 3.8 (R-3.5) (4.5 years)
License	MIT + file LICENSE
Depends	R (>= 3.5.0), grid, Homo.sapiens, TxDb.Hsapiens.UCSC.hg38.knownGene
Imports	igraph, biomaRt, Rcpp, data.table, OrganismDbi, AnnotationDbi, grDevices, stats, utils, GenomicRanges, IRanges
LinkingTo	Rcpp
Suggests	knitr, rmarkdown, BiocStyle, testthat
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Package Archives

Follow Installation instructions to use this package in your R session.

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Source Repository	git clone https://git.bioconductor.org/packages/gpart
Source Repository (Developer Access)	git clone [email protected]:packages/gpart
Package Short Url	https://bioconductor.org/packages/gpart/
Package Downloads Report	Download Stats