Package Recipe 'bioconductor-ptairms'

recipe bioconductor-ptairms

Pre-processing PTR-TOF-MS Data

Homepage:: https://bioconductor.org/packages/3.20/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:

1.18.0-0, 1.14.0-0, 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,

1.18.0-0, 1.14.0-0, 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:

on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biobase >=2.70.0,<2.71.0a0
on bioconductor-msnbase >=2.36.0,<2.37.0
on bioconductor-msnbase >=2.36.0,<2.37.0a0
on bioconductor-rhdf5 >=2.54.0,<2.55.0
on bioconductor-rhdf5 >=2.54.1,<2.55.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-bit64
on r-chron
on r-data.table
on r-doparallel
on r-dt
on r-envipat
on r-foreach
on r-ggplot2
on r-ggpubr
on r-gridextra
on r-hmisc
on r-minpack.lm
on r-plotly
on r-rcpp
on r-rlang
on r-scales
on r-shiny
on r-shinyscreenshot
on r-signal

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-ptairms

to add into an existing workspace instead, run:

pixi add bioconductor-ptairms

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-ptairms

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-ptairms

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-ptairms:<tag>

(see bioconductor-ptairms/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-ptairms/README.html)