@article {1593879,
	title = {DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species},
	journal = {Comput Struct Biotechnol J},
	volume = {19},
	year = {2021},
	month = {2021},
	pages = {2018-2026},
	abstract = {With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.},
	issn = {2001-0370},
	doi = {10.1016/j.csbj.2021.04.021},
	author = {Hu, Yanhui and Tattikota, Sudhir Gopal and Liu, Yifang and Comjean, Aram and Gao, Yue and Forman, Corey and Kim, Grace and Rodiger, Jonathan and Papatheodorou, Irene and Dos Santos, Gilberto and Mohr, Stephanie E and Perrimon, Norbert}
}
