recipe r-cnaqc

Copy number quality control

Homepage:

https://github.com/caravagnalab/CNAqc

Documentation:

https://caravagnalab.github.io/CNAqc/

License:

GPL3 / GPL-3.0-or-later

Recipe:

/r-cnaqc/meta.yaml

CNAqc is a package to quality control (QC) bulk cancer sequencing data. Methods are available to , visualise and manipulate i) somatic mutation data of both single-nucleotide variants and insertion-deletions, ii) allele-specific Copy Number Alterations (CNAs) and iii) tumour purity estimates. QC procedures in CNAqc can be used to validate copy number segmentations against variant allele frequencies of somatic mutations; QC scores can be used to rank alternative tumour segmentations and purity/ ploidy estimates. CNAqc provides also algorithms to phase mutation multiplicities against CNAs and estimate Cancer Cell Fractions (CCFs) with their uncertainty. The package contains also statistical tests to identify patterns of over-fragmentation of chromosome arms (excessively short and numerous DNA fragments) and perform various manipulation tasks for somatic tumour data.

package r-cnaqc

(downloads) docker_r-cnaqc

Versions:

1.1.3-01.1.2-0

Depends:
  • on bioconductor-annotationdbi

  • on bioconductor-complexheatmap

  • on bioconductor-genomicranges

  • on bioconductor-rhtslib

  • on bioconductor-rsamtools

  • on bioconductor-variantannotation

  • on r-akima

  • on r-base >=4.4,<4.5.0a0

  • on r-bmix

  • on r-cli

  • on r-clisymbols

  • on r-cowplot

  • on r-crayon

  • on r-data.table

  • on r-dplyr

  • on r-easypar

  • on r-ggplot2

  • on r-ggpubr

  • on r-ggrepel

  • on r-ggsci

  • on r-gtools

  • on r-magrittr

  • on r-peakpick

  • on r-pio

  • on r-progress

  • on r-r.utils

  • on r-rcolorbrewer

  • on r-readr

  • on r-scales

  • on r-tibble

  • on r-tidyr

  • on r-vcfr

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 r-cnaqc

to add into an existing workspace instead, run:

pixi add r-cnaqc

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 r-cnaqc

Alternatively, to install into a new environment, run:

conda create -n envname r-cnaqc

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/r-cnaqc:<tag>

(see r-cnaqc/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.

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