R.SamBada

R.SamBada performs automated landscape genomic analyses by interfacing with samβada to detect genome–environment associations and candidate genes involved in local adaptation.

Key Features:

• Genome–environment association (samβada): Interfaces with samβada to perform genome–environment association tests for detecting signatures of local adaptation.
• Environmental data retrieval: Automates retrieval of environmental conditions at sampling locations for use in association analyses.
• Gene annotation (Ensembl): Annotates candidate loci using the Ensembl genome browser to link variants to genes.
• Pre- and post-processing automation: Automates pre-processing and post-processing steps commonly required in landscape genomic workflows.
• Standardization and reproducibility: Standardizes the analysis pipeline to enhance reproducibility of landscape genomic studies.
• Case study applications: Has been applied to sheep from Morocco (no evident population structure) and Lidia cattle from Spain (population substructuring) to identify candidate genes related to local adaptation.

Scientific Applications:

• Local adaptation discovery: Identifies genetic variants and candidate genes associated with environmental variables reflecting local adaptation.
• Evolutionary and population genomics: Supports studies of adaptive processes and population structure in wild and domesticated species.
• Conservation genomics: Informs conservation strategies by highlighting genetic factors relevant to species persistence under environmental change.

Methodology:

Automates retrieval of environmental data at sampling sites, runs samβada genome–environment association analyses, performs automated pre- and post-processing, and annotates candidate loci using the Ensembl genome browser.