FlyAnatoView: Visualization of Drosophila Single-cell RNA-seq Datasets on Anatomographs
- 1Harvard Medical School
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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BibTeX
@misc{hu2026flyanatoview,
title = {{FlyAnatoView: Visualization of Drosophila Single-cell RNA-seq Datasets on Anatomographs}},
author = {Y. Hu and J. Kalina and A. Veal and B. Ewen-Campen and T. Porter and J. Song and Y. Luo and K. Huang and D. Goutte-Gattat and N. H. Brown and I. Papatheodorou and N. Perrimon},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.28.755010},
url = {https://www.biorxiv.org/content/10.64898/2026.09.28.755010v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - FlyAnatoView: Visualization of Drosophila Single-cell RNA-seq Datasets on Anatomographs
AU - Y. Hu
AU - J. Kalina
AU - A. Veal
AU - B. Ewen-Campen
AU - T. Porter
AU - J. Song
AU - Y. Luo
AU - K. Huang
AU - D. Goutte-Gattat
AU - N. H. Brown
AU - I. Papatheodorou
AU - N. Perrimon
PY - 2026
DA - 2026/09/28
PB - bioRxiv
DO - 10.64898/2026.09.28.755010
UR - https://www.biorxiv.org/content/10.64898/2026.09.28.755010v1
AB - 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.
ER -