Package Recipe 'bioconductor-nanotator'

recipe bioconductor-nanotator

Next generation structural variant annotation and classification

Homepage:: https://bioconductor.org/packages/3.18/bioc/html/nanotatoR.html
License:: file LICENSE
Recipe:: /bioconductor-nanotator/meta.yaml

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.

package bioconductor-nanotator¶

Versions:

1.18.0-0, 1.16.0-0, 1.14.0-0, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.4.0-0, 1.2.0-0,

1.18.0-0, 1.16.0-0, 1.14.0-0, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-1

Depends:

on bioconductor-annotationdbi >=1.64.0,<1.65.0
on bioconductor-genomicranges >=1.54.0,<1.55.0
on bioconductor-org.hs.eg.db >=3.18.0,<3.19.0
on r-base >=4.3,<4.4.0a0
on r-curl
on r-dplyr
on r-hash >=2.2.6
on r-httr
on r-knitr
on r-openxlsx >=4.0.17
on r-rentrez >=1.1.0
on r-rlang
on r-stringr
on r-testthat
on r-tidyverse
on r-varfrompdb
on r-xml
on r-xml2r

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-nanotator

to add into an existing workspace instead, run:

pixi add bioconductor-nanotator

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-nanotator

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-nanotator

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-nanotator:<tag>

(see bioconductor-nanotator/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-nanotator/README.html)