MOTIVATION: The HLA system plays a pivotal role in both clinical applications and immunology research. Typing HLA genes in patient and donor is indeed required in hematopoietic stem cell and solid-organ transplantation, and the histocompatibility complex region exhibits countless genetic associations with immune-related pathologies. Since the discovery of HLA antigens, the HLA system nomenclature and typing methods have constantly evolved, which leads to difficulties in using data generated with older methodologies. RESULTS: Here, we present Easy-HLA, a web-based software suite designed to facilitate analysis and gain knowledge from HLA typing, regardless of nomenclature or typing method. Easy-HLA implements a computational and statistical method of HLA haplotypes inference based on published reference populations containing over 600 000 haplotypes to upgrade missing or partial HLA information: 'HLA-Upgrade' tool infers high-resolution HLA typing and 'HLA-2-Haplo' imputes haplotype pairs and provides additional functional annotations (e.g. amino acids and KIR ligands). We validated both tools using two independent cohorts (total n = 2500). For HLA-Upgrade, we reached a prediction accuracy of 92% from low- to high-resolution of European genotypes. We observed a 96% call rate and 76% accuracy with HLA-2-Haplo European haplotype pairs prediction. In conclusion, Easy-HLA tools facilitate large-scale immunogenetic analysis and promotes the multi-faceted HLA expertise beyond allelic associations by providing new functional immunogenomics parameters. AVAILABILITY AND IMPLEMENTATION: Easy-HLA is a web application freely available (free account) at: https://hla.univ-nantes.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: The 1000 Genomes (1KG) Project provides a near-comprehensive resource on human genetic variation in worldwide reference populations. 1KG variants can be accessed through a browser and through the raw and annotated data that are regularly released on an ftp server. We developed Ferret, a user-friendly Java tool, to easily extract genetic variation information from these large and complex data files. From a locus, gene(s) or SNP(s) of interest, Ferret retrieves genotype data for 1KG SNPs and indels, and computes allelic frequencies for 1KG populations and optionally, for the Exome Sequencing Project populations. By converting the 1KG data into files that can be imported into popular pre-existing tools (e.g. PLINK and HaploView), Ferret offers a straightforward way, even for non-bioinformatics specialists, to manipulate, explore and merge 1KG data with the user's dataset, as well as visualize linkage disequilibrium pattern, infer haplotypes and design tagSNPs. AVAILABILITY AND IMPLEMENTATION: Ferret tool and source code are publicly available at http://limousophie35.github.io/Ferret/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.