R

R-package

The aim of the eggbiomechanic package is to allow a rapid and reproducible analysis of the biomechanical parameters of the chicken egg.

https://explore-metabar.sk8.inrae.fr/

F3MR is a R package that help to analyze food microbiome omics data based on dedicated and curated metabolic modules based on extensive literature review. It belongs to F3M software suite developed by INRAE Food Microbial Ecology lab

FreezeR is a R package which implements a Bayesian model aiming at deciphering main drivers of tree buds freezing.

The aim of this package is to provide a full genomic features annotation from genomic coordinates, without use an annotation priority.

This repository moved to https://gitlab.cirad.fr/astre/geonetwork

https://metatoul.pages.mia.inra.fr/graphstats

Landscape Epidemiology and Evolution R package

Docs

CRAN

Shiny app || Shiny Multi app

Produce an epidemiological risk map by weighting multiple risk factors. https://umr-astre.pages.mia.inra.fr/mapMCDA/

The goal of this package is to help users in using Capsis software and compile reports for field workshops. The workshop consist in predicting management effects on forest stand with Samsara2 model within Capsis platform.

http://martelosim.lessem.forge.inrae.fr/

R package for modelling arthropod development rates (mean and variance) as a function of temperature in nimble. Adapted from the PhD work of Soledad Castano (http://www.theses.fr/223623849).

PatHways lOngitudianal and diffErential aNanlysis in metabolomICS (PHOENICS). Perform differential analysis of metabolic pathways based on longitudinal metabolomics data.

https://umrf.pages.mia.inra.fr/ranomaly/

R package to run MuSICA

This project is the source repository of the CRAN package 'hicream' https://cran.r-project.org/package=hicream.

It performs Hi-C data differential analysis based on pixel-level differential analysis and a post hoc inference strategy to quantify signal in clusters of pixels. Clusters of pixels are obtained through a connectivity-constrained two-dimensional hierarchical clustering.

mixKernel is a multiple kernel framework that allows to integrate multiple datasets of various types into a single analysis. The package is published on CRAN: https://cran.r-project.org/package=mixKernel