recipe bioconductor-ptairms

Pre-processing PTR-TOF-MS Data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/ptairMS.html

License:

GPL-3

Recipe:

/bioconductor-ptairms/meta.yaml

This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the 'sample by features' table of peak intensities in addition to the sample and feature metadata (as a singl<e ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and quantification, feature alignment, missing value imputation and feature annotation. Applications to exhaled air and cell culture in headspace are described in the vignettes and examples. This package was used for data analysis of Gassin Delyle study on adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS), and permit to identfy four potentiel biomarquers of the infection.

package bioconductor-ptairms

versions:

1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.2.0-2,  1.2.0-1,  1.2.0-0,  1.0.0-0

depends bioconductor-biobase:

>=2.62.0,<2.63.0

depends bioconductor-biobase:

>=2.62.0,<2.63.0a0

depends bioconductor-msnbase:

>=2.28.0,<2.29.0

depends bioconductor-msnbase:

>=2.28.1,<2.29.0a0

depends bioconductor-rhdf5:

>=2.46.0,<2.47.0

depends bioconductor-rhdf5:

>=2.46.1,<2.47.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx-ng:

>=12

depends r-base:

>=4.3,<4.4.0a0

depends r-bit64:

depends r-chron:

depends r-data.table:

depends r-doparallel:

depends r-dt:

depends r-envipat:

depends r-foreach:

depends r-ggplot2:

depends r-ggpubr:

depends r-gridextra:

depends r-hmisc:

depends r-minpack.lm:

depends r-plotly:

depends r-rcpp:

depends r-rlang:

depends r-scales:

depends r-shiny:

depends r-shinyscreenshot:

depends r-signal:

requirements:

additional platforms:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-ptairms

and update with::

   mamba update bioconductor-ptairms

To create a new environment, run:

mamba create --name myenvname bioconductor-ptairms

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

(see `bioconductor-ptairms/tags`_ for valid values for ``<tag>``)

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