As the basic units of life, cells present dramatic heterogeneity which, although crucial to an organism's behavior, is undetected by bulk analysis. Recently, much attention has been paid to reveal cellular types and states at the single-cell level including genome, transcriptome, epigenome or proteome-based on sequencing and immunological methods, etc. Among these approaches, transcriptomic analysis provides knowledge of the molecular linkages between genetic information and the proteome, leading to a comprehensive understanding of biological processes and diseases. Compared to single-dimensional inspection, multi-dimensional analysis combines the transcriptome with other "omics" to enable a comprehensive understanding of single-cell processes and functions. Moreover, compared to separate observations or single snapshots, spatial dimension and lineage time tracing can provide a more multifaceted understanding of the micro-environment and dynamic processes. In this review, we will introduce current transcriptomic analysis methods, as well as their combination with other omics methods including genomic, proteomic, and epigenetic approaches. Multi-dimensional analysis using these approaches for spatial positioning and lineage tracing applications will be reviewed. The future perspectives of single-cell multi-omics analysis based on the transcriptome will also be discussed.