MOTIVATION: Recent advances in transcriptomics have enabled unprecedented insight into gene expression analysis at a single-cell resolution. While it is anticipated that the number of publications based on such technologies will increase in the next decade, there is currently no public resource to centralize and enable scientists to explore single-cell datasets published in the field of reproductive biology. RESULTS: Here, we present a major update of the ReproGenomics Viewer, a cross-species and cross-technology web-based resource of manually-curated sequencing datasets related to reproduction. The redesign of the ReproGenomics Viewer's architecture is accompanied by significant growth of the database content including several landmark single-cell RNA-sequencing datasets. The implementation of additional tools enables users to visualize and browse the complex, high-dimensional data now being generated in the reproductive field. AVAILABILITY AND IMPLEMENTATION: The ReproGenomics Viewer resource is freely accessible at http://rgv.genouest.org. The website is implemented in Python, JavaScript and MongoDB, and is compatible with all major browsers. Source codes can be downloaded from https://github.com/fchalmel/RGV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: GOAnno is a web tool that automatically annotates proteins according to the Gene Ontology (GO) using evolutionary information available in hierarchized multiple alignments. GO terms present in the aligned functional subfamily can be cross-validated and propagated to obtain highly reliable predicted GO annotation based on the GOAnno algorithm. AVAILABILITY: The web tool and a reduced version for local installation are freely available at http://igbmc.u-strasbg.fr/GOAnno/GOAnno.html SUPPLEMENTARY INFORMATION: The website supplies a detailed explanation and illustration of the algorithm at http://igbmc.u-strasbg.fr/GOAnno/GOAnnoHelp.html.