CALANGO: A phylogeny-aware comparative genomics tool for discovering quantitative genotype-phenotype associations across species.

Living species vary significantly in phenotype and genomic content. Sophisticated statistical methods linking genes with phenotypes within a species have led to breakthroughs in complex genetic diseases and genetic breeding. Despite the abundance of genomic and phenotypic data available for thousands of species, finding genotype-phenotype associations across species is challenging due to the non-independence of species data resulting from common ancestry.

Genome-Wide Survey of Genes Under Positive Selection in Avian Pathogenic Escherichia coli Strains.

The ability to obtain bacterial genomes from the same host has allowed for comparative studies that help in the understanding of the molecular evolution of specific pathotypes. Avian pathogenic Escherichia coli (APEC) is a group of extraintestinal strains responsible for causing colibacillosis in birds. APEC is also suggested to possess a role as a zoonotic agent.

POTION: an end-to-end pipeline for positive Darwinian selection detection in genome-scale data through phylogenetic comparison of protein-coding genes.

Background: Detection of genes evolving under positive Darwinian evolution in genome-scale data is nowadays a prevailing strategy in comparative genomics studies to identify genes potentially involved in adaptation processes. Despite the large number of studies aiming to detect and contextualize such gene sets, there is virtually no software available to perform this task in a general, automatic, large-scale and reliable manner. This certainly occurs due to the computational challenges involved in this task, such as the appropriate modeling of data under analysis, the computation time to perform several of the required steps when dealing with genome-scale data and the highly error-prone nature of the sequence and alignment data structures needed for genome-wide positive selection detection.