Year: 2026
Type: preprint
Abstract: ABSTRACT Single-cell RNA sequencing (scRNA-seq) is a powerful approach for characterizing gene expression at single-cell resolution and identifying distinct cell populations within complex tissues. However, tissue dissociation disrupts the spatial relationships among cells, making it difficult to determine their original anatomical locations and interpret gene expression patterns in the context of tissue organization. To address this limitation, we developed FlyAnatoView ( https://www.flyrnai.org/tools/rna_seq_base/web/svg_files/ ), a resource that projects scRNA-seq data onto anatomical diagrams of Drosophila melanogaster . By integrating gene expression data with anatomical representations, FlyAnatoView helps restore spatial context and enables users to explore expression patterns across tissues, organs, and cell types. This resource provides an intuitive way to connect transcriptomic profiles with anatomical structures, facilitating the interpretation and exploration of scRNA-seq datasets.
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: BBSRC-NSF/BIO: Integrative analysis and Visualisation of Fly Cell Atlas datasets to enable cross-species comparisons, G2137052142, BBSRC-NSF/BIO: Integrative analysis and Visualisation of Fly Cell Atlas datasets to enable cross-species comparisons, BBSRC-NSF/BIO: Integrative analysis and Visualisation of Fly Cell Atlas datasets to enable cross-species comparisons
OpenAlex ID: W7218472839