The newly developed technologies for profiling cellular heterogeneity have spurred a world-wide pursuit of single-cell analysis in the field of omics studies, investigating the genome, epigenome, transcriptome, proteome, metabo-lome, and their inherent interactions. Knowledge obtained through such analysis facilitates a deeper understanding of how underlying molecular and architectural changes alter cell behaviors, development, and disease processes. Geno-me-scale amplification of genomic DNAs or cDNAs from mRNAs transcribed in single cells allows for the mea-surement of genetic alterations and cell types at an un-precedented level. The emerging microchip-based tools for single-cell omics analysis further enable the evaluation of cellular omics with high throughput, improved sensitivity, and reduced cost. On the other hand, single-cell high-di-mensional data obtained with high-throughput technologies also pose new challenges in bioinformatics to analyze, process, and make sense of the big data, in order to deliver new biological insights and knowledge.