Species distribution modelling using latent Gaussian random
fields
Functions to fit, visualise and compare Gaussian Random
Field species distribution models.

Functions to fit, visualise and compare Gaussian random
field species distribution models.

Functions to fit, visualise and compare Gaussian random field species distribution models.

c(person("Camila", "Garcia-Echeverri", email = "cagarciae@unal.edu.co", comment = c(ORCID = "0000-0001-8227-7684"),role = c("aut", "cre")),
person("Maria", "Arenas-Bautista", email = "mcarenasb@unal.edu.co", comment = c(ORCID = "0000-0003-1578-5157"), role = c("cot")),
person("Leonardo", "Donado", email = "lddonadog@unal.edu.co", comment=c(ORCID = "0000-0002-5479-3419" ), role = c("cot")))
A tool to sensitivity analysis using SOBOL (Sobol, 1993) and AMA (Dell'Oca et al. 2017 <doi:10.5194/hess-21-6219-2017>) indices.
It allows to identify the most sensitive parameter or parameters of a model.
Camila Garcia-Echeverri [aut, cre]
(<https://orcid.org/0000-0001-8227-7684>),
Maria Arenas-Bautista [cot] (<https://orcid.org/0000-0003-1578-5157>),
Leonardo Donado [cot] (<https://orcid.org/0000-0002-5479-3419>)

Computation of Quantitative Trait Loci hits in the selected gene set. Performing gene set validation with Quantitative Trait Loci information. Performing gene set enrichment analysis with available Quantitative Trait Loci data and computation of statistical significance value from gene set analysis. Obtaining the list of Quantitative Trait Loci hit genes along with their overlapped Quantitative Trait Loci names.

Gene Set Analysis with Fisher Combined Method
Provides the p-value for a joint test of association between a phenotype and a set of genetic variants (SNPs) by combining marginal p-values using the Fisher method. See Fisher, R.A. (1925,ISBN:0-05-002170-2) Statistical Methods for Research Workers.

Gene Set Analysis using the Gamma Method
GSAgm is an R package that completes a self-contained gene set analysis (GSA) for RNA-seq and SNP data using the Gamma Method.