HTCA: a database with an in-depth characterization of the single-cell human transcriptome

• Main Authors: Pan, Lu, Shan, Shaobo, Tremmel, Roman, Li, Weiyuan, Liao, Zehuan, Shi, Hangyu, Chen, Qishuang, Zhang, Xiaolu, Li, Xuexin
• Other Authors: School of Biological Sciences
• Format: Article
• Language: English
• Published: 2023
• Subjects: Science::Biological sciences; HTCA Database; Gene Ontology
• Online Access: https://hdl.handle.net/10356/169452
• Institution: Nanyang Technological University

Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to consolidate published data, yet extensive characterization is still lacking. Many focused on raw-data database constructions while others concentrate mainly on gene expression queries. Hereby, we present HTCA (www.htcatlas.org), an interactive database constructed based on ∼2.3 million high-quality cells from ∼3000 scRNA-seq samples and comprised in-depth phenotype profiles of 19 healthy adult and matching fetal tissues. HTCA provides a one-stop interactive query to gene signatures, transcription factor (TF) activities, TF motifs, receptor-ligand interactions, enriched gene ontology (GO) terms, etc. across cell types in adult and fetal tissues. At the same time, HTCA encompasses single-cell splicing variant profiles of 16 adult and fetal tissues, spatial transcriptomics profiles of 11 adult and fetal tissues, and single-cell ATAC-sequencing (scATAC-seq) profiles of 27 adult and fetal tissues. Besides, HTCA provides online analysis tools to perform major steps in a typical scRNA-seq analysis. Altogether, HTCA allows real-time explorations of multi-omics adult and fetal phenotypic profiles and provides tools for a flexible scRNA-seq analysis.