uncoverappLib

This is the development version of uncoverappLib; for the stable release version, see uncoverappLib.

Interactive graphical application for clinical assessment of sequence coverage at the base-pair level

Bioconductor version: Development (3.19)

a Shiny application containing a suite of graphical and statistical tools to support clinical assessment of low coverage regions.It displays three web pages each providing a different analysis module: Coverage analysis, calculate AF by allele frequency app and binomial distribution. uncoverAPP provides a statisticl summary of coverage given target file or genes name.

Author: Emanuela Iovino [cre, aut], Tommaso Pippucci [aut]

Maintainer: Emanuela Iovino <emanuela.iovino at unibo.it>

Citation (from within R, enter citation("uncoverappLib")):

Installation

To install this package, start R (version "4.4") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("uncoverappLib")

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

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Annotation, Coverage, Software, Visualization
Version	1.13.0
In Bioconductor since	BioC 3.12 (R-4.0) (3.5 years)
License	MIT + file LICENSE
Depends
Imports	markdown, shiny, shinyjs, shinyBS, shinyWidgets, shinycssloaders, DT, Gviz, Homo.sapiens, openxlsx, condformat, stringr, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg38.knownGene, BiocFileCache, rappdirs, TxDb.Hsapiens.UCSC.hg19.knownGene, rlist, utils, S4Vectors, EnsDb.Hsapiens.v75, EnsDb.Hsapiens.v86, OrganismDbi, processx, Rsamtools, GenomicRanges
System Requirements
URL	https://github.com/Manuelaio/uncoverappLib
Bug Reports	https://github.com/Manuelaio/uncoverappLib/issues

Suggests	BiocStyle, knitr, testthat, rmarkdown, dplyr
Linking To
Enhances
Depends On Me
Imports Me
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Build Report	Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/uncoverappLib
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/uncoverappLib
Package Short Url	https://bioconductor.org/packages/uncoverappLib/
Package Downloads Report	Download Stats