Annotation of cell types (ACT): a convenient web server for cell type annotation.

BACKGROUND: The advancement of single-cell sequencing has progressed our ability to solve biological questions. Cell type annotation is of vital importance to this process, allowing for the analysis and interpretation of enormous single-cell datasets. At present, however, manual cell annotation which is the predominant approach remains limited by both speed and the requirement of expert knowledge. METHODS: To address these challenges, we constructed a hierarchically organized marker map through manually curating over 26,000 cell marker entries from about 7000 publications. We then developed WISE, a weighted and integrated gene set enrichment method, to integrate the prevalence of canonical markers and ordered differentially expressed genes of specific cell types in the marker map. Benchmarking analysis suggested that our method outperformed state-of-the-art methods. RESULTS: By integrating the marker map and WISE, we developed a user-friendly and convenient web server, ACT ( http://xteam.xbio.top/ACT/ or http://biocc.hrbmu.edu.cn/ACT/ ), which only takes a simple list of upregulated genes as input and provides interactive hierarchy maps, together with well-designed charts and statistical information, to accelerate the assignment of cell identities and made the results comparable to expert manual annotation. Besides, a pan-tissue marker map was constructed to assist in cell assignments in less-studied tissues. Applying ACT to three case studies showed that all cell clusters were quickly and accurately annotated, and multi-level and more refined cell types were identified. CONCLUSIONS: We developed a knowledge-based resource and a corresponding method, together with an intuitive graphical web interface, for cell type annotation. We believe that ACT, emerging as a powerful tool for cell type annotation, would be widely used in single-cell research and considerably accelerate the process of cell type identification.

Single-cell RNA-seq reveals the invasive trajectory and molecular cascades underlying glioblastoma progression.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor, in which GBM stem cells (GSCs) were identified to contribute to aggressive phenotypes and poor prognosis. Yet, how GSCs progress to invasive cells remains largely unexplored. Here, we revealed the cell subpopulations with distinct functional status and the existence of cells with high invasive potential within heterogeneous primary GBM tumors. We reconstructed a branched trajectory by pseudotemporal ordering of single tumor cells, in which the root showed GSC-like phenotype while the end displayed high invasive activity. Thus, we further determined a path along which GSCs gradually transformed to invasive cells, called the 'stem-to-invasion path'. Along this path, cells showed incremental expression of GBM invasion-associated signatures and diminishing expression of GBM stem cell markers. These findings were validated in an independent single-cell data set of GBM. Through analyzing the molecular cascades underlying the path, we identify crucial factors controlling the attainment of invasive potential of tumor cells, including transcription factors and long noncoding RNAs. Our work provides novel insights into GBM progression, especially the attainment of invasive potential in primary tumor cells, and supports the cancer stem cell model, with valuable implications for GBM therapy.