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  "Title": "Postprocessing and univariate analysis of omics data",
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  "Description": "The 'phenomis' package provides methods to perform\npost-processing (i.e. quality control and normalization) as\nwell as univariate statistical analysis of single and\nmulti-omics data sets. These methods include quality control\nmetrics, signal drift and batch effect correction, intensity\ntransformation, univariate hypothesis testing, but also\nclustering (as well as annotation of metabolomics data). The\ndata are handled in the standard Bioconductor formats (i.e.\nSummarizedExperiment and MultiAssayExperiment for single and\nmulti-omics datasets, respectively). As a result, all methods\ncan be readily chained as workflows. The pipeline can be\nfurther enriched by multivariate analysis and feature\nselection, by using the 'ropls' and 'biosigner' packages, which\nsupport the same formats. Data can be conveniently imported\nfrom and exported to text files. Although the methods were\ninitially targeted to metabolomics data, most of the methods\ncan be applied to other types of omics data (e.g.,\ntranscriptomics, proteomics).",
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  "Author": "Etienne A. Thevenot [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-1019-4577>),\nNatacha Lenuzza [ctb],\nMarie Tremblay-Franco [ctb],\nAlyssa Imbert [ctb],\nPierrick Roger [ctb],\nEric Venot [ctb],\nSylvain Dechaumet [ctb]",
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        "phenomis"
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        "filtering,SummarizedExperiment-method"
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      "title": "phenomis: Postprocessing and univariate statistical analysis of omics data",
      "author": "Etienne A. Thevenot",
      "engine": "knitr::rmarkdown",
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        "Introduction",
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        "Importing from/exporting to tabular files",
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