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cff-version: 1.2.0
message: 'To cite package "phenomis" in publications use:'
type: software
license: CECILL-1.0
title: 'phenomis: Postprocessing and univariate analysis of omics data'
version: 1.7.2
abstract: The 'phenomis' package provides methods to perform post-processing (i.e.
  quality control and normalization) as well as univariate statistical analysis of
  single and multi-omics data sets. These methods include quality control metrics,
  signal drift and batch effect correction, intensity transformation, univariate hypothesis
  testing, but also clustering (as well as annotation of metabolomics data). The data
  are handled in the standard Bioconductor formats (i.e. SummarizedExperiment and
  MultiAssayExperiment for single and multi-omics datasets, respectively; the alternative
  ExpressionSet and MultiDataSet formats are also supported for convenience). As a
  result, all methods can be readily chained as workflows. The pipeline can be further
  enriched by multivariate analysis and feature selection, by using the 'ropls' and
  'biosigner' packages, which support the same formats. Data can be conveniently imported
  from and exported to text files. Although the methods were initially targeted to
  metabolomics data, most of the methods can be applied to other types of omics data
  (e.g., transcriptomics, proteomics).
authors:
- family-names: Thevenot
  given-names: Etienne A.
  email: etienne.thevenot@cea.fr
  orcid: https://orcid.org/0000-0003-1019-4577
repository: https://bioc.r-universe.dev
url: https://doi.org/10.1038/s41597-021-01095-3
date-released: '2024-07-08'
contact:
- family-names: Thevenot
  given-names: Etienne A.
  email: etienne.thevenot@cea.fr
  orcid: https://orcid.org/0000-0003-1019-4577