nanotatoR

DOI: 10.18129/B9.bioc.nanotatoR    

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

Next generation structural variant annotation and classification

Bioconductor version: Development (3.14)

Whole genome sequencing (WGS) has successfully been used to identify single-nucleotide variants (SNV), small insertions and deletions (INDELs) and, more recently, small copy number variants (CNVs). However, due to utilization of short reads, it is not well suited for identification of structural variants (SV). Optical mapping (OM) from Bionano Genomics, utilizes long fluorescently labeled megabase size DNA molecules for de novo genome assembly and identification of SVs with a much higher sensitivity than WGS. Nevertheless, currently available SV annotation tools have limited number of functions. NanotatoR is an R package written to provide a set of annotations for SVs identified by OM. It uses Database of Genomic Variants (DGV), Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources (DECIPHER) as well as a subset (154 samples) of 1000 Genome Project to calculate the population frequencies of the SVs (an optional internal cohort SV frequency calculation is also available). NanotatoR creates a primary gene list (PG) from NCBI databases based on proband’s phenotype specific keywords and compares the list to the set of genes overlapping/near SVs. The output is given in an Excel file format, which is subdivided into multiple sheets based on SV type (e.g., INDELs, Inversions, Translocations). Users then have a choice to filter SVs using the provided annotations for de novo (if parental samples are available) or inherited rare variants.

Author: Surajit Bhattacharya, Hayk Barsheghyan, Emmanuele C Delot and Eric Vilain

Maintainer: Surajit Bhattacharya <sbhattach2 at childrensnational.org>

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

Installation

To install this package, start R (version "4.1") and enter:

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

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

BiocManager::install("nanotatoR")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("nanotatoR")

 

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Details

biocViews GenomeAssembly, Software, VariantAnnotation, WorkflowStep
Version 1.9.1
In Bioconductor since BioC 3.9 (R-3.6) (2.5 years)
License file LICENSE
Depends R (>= 4.1)
Imports hash (>= 2.2.6), openxlsx (>= 4.0.17), rentrez (>= 1.1.0), stats, rlang, stringr, knitr, testthat, utils, AnnotationDbi, httr, GenomicRanges, tidyverse, VarfromPDB, org.Hs.eg.db, curl, dplyr, XML, XML2R
LinkingTo
Suggests rmarkdown, yaml
SystemRequirements
Enhances
URL https://github.com/VilainLab/nanotatoR
BugReports https://github.com/VilainLab/nanotatoR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package nanotatoR_1.9.1.tar.gz
Windows Binary nanotatoR_1.9.1.zip
macOS 10.13 (High Sierra) nanotatoR_1.9.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/nanotatoR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/nanotatoR
Package Short Url https://bioconductor.org/packages/nanotatoR/
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