Stereo-seq - Drosophila embryo E6_3

Stereo-seq faithfully captures Drosophila spatial transcriptomes with high resolution

zenodo_spatial

Info

zenodo_spatial/stereoseq/drosophila_embryo_e6_3
Wang et al. (2022)
2.23 MiB
23-09-2024
1248 cells × 873 genes

Used in

Description

Drosophila has long been a successful model organism in multiple biomedical fields. Spatial gene expression patterns are critical for the understanding of complex pathways and interactions, whereas temporal gene expression changes are vital for studying highly dynamic physiological activities. Systematic studies in Drosophila are still impeded by the lack of spatiotemporal transcriptomic information. Here, utilizing spatial enhanced resolution omics-sequencing (Stereo-seq), we dissected the spatiotemporal transcriptomic changes of developing Drosophila with high resolution and sensitivity. (Data from an embryo collected 14-16 h after egg laying)

Preview

dataset is an AnnData object with n_obs × n_vars = 1248 × 873 with slots:

Reference

Name Description Type Data type Size
var
feature_name A human-readable name for the feature, usually a gene symbol. vector object 873
layers
counts Raw counts sparsematrix int64 1248 × 873
uns
dataset_description Long description of the dataset. atomic str 1
dataset_id A unique identifier for the dataset. This is different from the obs.dataset_id field, which is the identifier for the dataset from which the cell data is derived. atomic str 1
dataset_name A human-readable name for the dataset. atomic str 1
dataset_organism The organism of the sample in the dataset. atomic str 1
dataset_reference Bibtex reference of the paper in which the dataset was published. atomic str 1
dataset_summary Short description of the dataset. atomic str 1
dataset_url Link to the original source of the dataset. atomic str 1

References

Wang, Mingyue, Qinan Hu, Tianhang Lv, Yuhang Wang, Qing Lan, Rong Xiang, Zhencheng Tu, et al. 2022. “High-Resolution 3D Spatiotemporal Transcriptomic Maps of Developing Drosophila Embryos and Larvae.” Developmental Cell 57 (10): 1271–1283.e4. https://doi.org/10.1016/j.devcel.2022.04.006.