DRomics - 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 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 continuous omics data (such as 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 normal distribution for each dose or concentration, with a common standard error. For further details see Delignette-Muller et al (2023) <DOI:10.24072/pcjournal.325> and Larras et al (2018) <DOI:10.1021/acs.est.8b04752>.

Last updated 2 days ago

6.08 score 5 stars 7 scripts 381 downloads

Interatrix - Compute Chi-Square Measures with Corrections

Chi-square tests are computed with corrections.

Last updated 23 days ago

4.40 score 8 scripts 257 downloads

fitdistrplus - Help to Fit of a Parametric Distribution to Non-Censored or Censored Data

Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.

Last updated 29 days ago

16.15 score 54 stars 153 dependents 4.5k scripts 56k downloads

nlstools - Tools for Nonlinear Regression Analysis

Several tools for assessing the quality of fit of a gaussian nonlinear model are provided.

Last updated 29 days ago

9.42 score 6 stars 7 dependents 528 scripts 2.6k downloads

kissDE - Retrieves Condition-Specific Variants in RNA-Seq Data

Retrieves condition-specific variants in RNA-seq data (SNVs, alternative-splicings, indels). It has been developed as a post-treatment of 'KisSplice' but can also be used with user's own data.

Last updated 5 months ago

alternativesplicingdifferentialsplicingexperimentaldesigngenomicvariationrnaseqtranscriptomics

5.98 score 3 stars 7 scripts 264 downloads

nlsMicrobio - Nonlinear Regression in Predictive Microbiology

Data sets and nonlinear regression models dedicated to predictive microbiology.

Last updated 29 days ago

5.57 score 1 stars 1 dependents 41 scripts 278 downloads

MareyMap - Estimation of Meiotic Recombination Rates Using Marey Maps

Local recombination rates are graphically estimated across a genome using Marey maps.

Last updated 30 days ago

5.30 score 1 stars 20 scripts 393 downloads

rbioacc - Inference and Prediction of ToxicoKinetic (TK) Models

The MOSAICbioacc application is a turnkey package providing bioaccumulation factors (BCF/BMF/BSAF) from a toxicokinetic (TK) model fitted to accumulation-depuration data. It is designed to fulfil the requirements of regulators when examining applications for market authorization of active substances. See Ratier et al. (2021) <doi:10.1101/2021.09.08.459421>.

Last updated 2 years ago

cpp

4.78 score 8 scripts 246 downloads

Mondrian - A Simple Graphical Representation of the Relative Occurrence and Co-Occurrence of Events

The unique function of this package allows representing in a single graph the relative occurrence and co-occurrence of events measured in a sample. As examples, the package was applied to describe the occurrence and co-occurrence of different species of bacterial or viral symbionts infecting arthropods at the individual level. The graphics allows determining the prevalence of each symbiont and the patterns of multiple infections (i.e. how different symbionts share or not the same individual hosts). We named the package after the famous painter as the graphical output recalls Mondrian’s paintings.

Last updated 9 months ago

4.00 score 2 stars 8 scripts 634 downloads