High-throughput sequencing (HTS)
High-throughput sequencing (HTS) is a technology that enables the rapid sequencing of DNA or RNA at a massive scale. In the context of KEA, HTS submission types cover a wide range of sequencing-based experiments, including transcriptomic and epigenomic profiling. These datasets are used to identify gene expression patterns, regulatory elements, epigenetic modifications, and cellular heterogeneity at both the bulk and single-cell levels. KEA also supports spatially resolved transcriptomic analyses.
Bulk sequencing (Bulk transcriptome / Epigenomic profiling)
Bulk sequencing refers to high-throughput sequencing performed on pooled populations of cells or tissues.
Bulk transcriptome: RNA sequencing data that quantify gene expression across cell populations, enabling differential expression analysis and functional annotation.
Epigenomic profiling: Sequencing assays such as ChIP-seq, ATAC-seq, DNase-seq, and bisulfite sequencing, which provide insights into chromatin accessibility, histone modifications, transcription factor binding, and DNA methylation landscapes.
Transcriptome profiling using RNA-sequencing (Ref. Haas, Brian J., and Michael C. Zody. "Advancing RNA-seq analysis." Nature biotechnology 28.5 (2010): 421-423.) Epigenomic profiling using ChIP-sequencing (Ref. Park, Peter J. "ChIP–seq: advantages and challenges of a maturing technology." Nature reviews genetics 10.10 (2009): 669-680.) Single-cell sequencing
Single-cell sequencing technologies decode genomic, transcriptomic, or epigenomic information at the level of individual cells. This approach enables the study of cellular heterogeneity, rare cell populations, lineage trajectories, and dynamic cell states in health and disease. In transcriptomics, single-cell RNA sequencing (scRNA-seq) provides gene expression profiles for thousands to millions of cells, while single-cell ATAC-seq or single-cell methylation assays extend these capabilities to the epigenome.
Spatial transcriptomics
Spatial transcriptomics refers to methods that measure gene expression while retaining the spatial information within intact tissues. Unlike bulk or single-cell RNA sequencing, spatial approaches integrate transcriptomic data with histological architecture.
Sequencing-based spatial methods (e.g., spatially barcoded RNA capture followed by NGS)
In situ hybridization or in situ sequencing methods (e.g., MERFISH, seqFISH), which directly capture gene expression within fixed tissue sections at subcellular resolution.
The schematic diagram shows the structure of a spatial transcriptomics study (Ref. Park, Jiwoon, et al. "Spatial omics technologies at multimodal and single cell/subcellular level." Genome biology 23.1 (2022): 256.) Microarray-based platforms measure gene expression, DNA methylation, or other genomic features using hybridization to probe sets fixed on a chip. Microarrays remain widely used for transcriptome profiling and epigenome analysis due to their cost-effectiveness and standardized protocols.
Schematic illustration of a simple microarray experimental design (Ref. Churchill, Gary A. "Fundamentals of experimental design for cDNA microarrays." Nature genetics 32.4 (2002): 490-495.) 
