FlyAnatoView: Visualization of Drosophila Single-cell RNA-seq Datasets on Anatomographs
Yanhui HuiD, Jenna Kalina, Austin Veal, Ben Ewen‐CampeniD, Tarryn PorteriD, Julia Song, Yicheng LuoiD, Kerui HuangiD, Damien Goutte-GattatiD, Nicholas H. BrowniD, Irene PapatheodorouiD, Norbert PerrimoniD
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.
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