한빛사논문
- 조회370
Karolina Hanna Prazanowska 1,2 & Su Bin Lim 1,2
1Department of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, 16499, Korea.
2Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, 16499, Korea.
Corresponding author : Correspondence to Su Bin Lim.
Abstract
As single-cell RNA sequencing (scRNA-seq) has emerged as a great tool for studying cellular heterogeneity within the past decade, the number of available scRNA-seq datasets also rapidly increased. However, reuse of such data is often problematic due to a small cohort size, limited cell types, and insufficient information on cell type classification. Here, we present a large integrated scRNA-seq dataset containing 224,611 cells from human primary non-small cell lung cancer (NSCLC) tumors. Using publicly available resources, we pre-processed and integrated seven independent scRNA-seq datasets using an anchor-based approach, with five datasets utilized as reference and the remaining two, as validation. We created two levels of annotation based on cell type-specific markers conserved across the datasets. To demonstrate usability of the integrated dataset, we created annotation predictions for the two validation datasets using our integrated reference. Additionally, we conducted a trajectory analysis on subsets of T cells and lung cancer cells. This integrated data may serve as a resource for studying NSCLC transcriptome at the single cell level.
논문정보
- Research article
- 2023년 03월 (BRIC 등록일 2023-03-28)
- 국내 연구진
- 생명과학 > 유전자발현
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