GAnnoViz: a cloud-integrated platform for chromosome-level feature annotation and visualization in biomedical multi-omics
image: (A) Hierarchical structure of the GFF3 format and the corresponding functions used for features’ extraction. (B) Comparison of the time consumed in parsing and visualizing multiple animal and plant genomic annotations. (C) The chromosomal location and alternative splice variants of the Atl3 gene in the human genome. (D) Linear representation of alternatively spliced Atl3 transcripts in mouse genome, including promoter regions and strand orientation. (E) Gene structures within the 7.40–7.52 Mb internal region of Chromosome 19. (F) Genomic context of Atl3 with multiple neighboring genes within 0.1 Mb flanking regions. (G) Distribution and functional annotation of protein domains in Atl3. (H) Genome-wide density profiles of genes and other genomic features, visualized as line and heat map plots.
Credit: Benben Miao, Yawei Shen, Hanjiao Luo, Guijia Liu, Xuan Luo, Caihuan Ke, Wei Dong, Jianfeng Li, Weiwei You
With multi-omics approaches increasingly employed to investigate multidimensional biological systems, current workflows often lack sufficient integration with the underlying genome, limiting comprehensive understanding of genomic structure and chromosomal preferences of candidate genes. Here, we present GAnnoViz (https://github.com/benben-miao/GAnnoViz/), a cloud-integrated framework for chromosome-level feature annotation and visualization in biomedical multi-omics, encompassing 30+ analytical and visualization modules across five key areas: acquisition of species genomic annotations, extraction of genomic features, drawing of gene structures, sliding window annotation, and chromosome-scale visualization of multi-omics. It supports genomic annotation retrieval for 349 species from Ensembl, GFF3 or GTF format compatibility, and an interactive interface deployed on the HiPlot cloud platform. Through three representative application scenarios, we demonstrated GAnnoViz flexibility in gene structure exploration and utility in annotating and visualizing transcriptomic and epigenomic results, bridging multi-omics findings with genome architecture for comprehensive biological interpretation at the chromosome scale.