Dose Response for Omics

Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of three replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated metabolomic data in log scale. In order to link responses across biological levels based on a common method, 'DRomics' also handles apical data as long as they are continuous and follow a Gaussian distribution for each dose or concentration, with a common standard error. For further details see Larras et al (2018) at < https://hal.archives-ouvertes.fr/hal-02309919>.


News

=== DRomics : Dose response for omics ===

Version 1.0-1

NEW FEATURES

  • Add of column yextrem in the results of drcfit (y value at the extremum for biphasic curves)

Version 1.0-0

  • Initial release.

Reference manual

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install.packages("DRomics")

2.1-3 by Aurelie Siberchicot, 3 days ago


https://lbbe.univ-lyon1.fr/-DRomics-.html, https://github.com/aursiber/DRomics


Browse source code at https://github.com/cran/DRomics


Authors: Marie-Laure Delignette-Muller [aut] , Elise Billoir [aut] , Floriane Larras [ctb] , Aurelie Siberchicot [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports stats, graphics, ggplot2

Depends on limma, utils, grDevices, DESeq2, SummarizedExperiment

Suggests parallel, shiny, shinyBS, shinyjs, testthat


See at CRAN