Single cell (sc) technologies offer an unprecedented level of investigation into cellular heterogeneity. Transcriptomic analyses are most commonly performed, but genome and epigenome can also be investigated at the sc level. Moreover, multi-omics technologies are developed to profile simultaneously different material from the same cell, enabling for example correlations between genomic mutations and alteration of gene expression. In parallel, spatial transcriptomics aim to combine transcriptomic and morphological information. The large amount of data generated require sophisticated bioinformatic analyses to extract biological meaning. Different algorithms are used to reconstitute cellular hierarchies along a pseudo-time axis offering a chance to characterise new, previously invisible, intermediate cell states.Genome and transcriptome sc technologies are commercially available, therefore these analyses are accessible to researchers. The focus will be placed here on transcriptome analyses, exploring the unique possibilities they bring, but also remaining hurdles. The requirements and pipeline for sample preparation will be discussed, along expected outcomes and modalities of analysis and resolution. Significant advances provided by sc analyses will be discussed, in the field of cancer, stem cell research and endocrine organs. In tumour, cellular hierarchies can be reconstructed from sc genomes, allowing resolution to the cell(s) and mutation(s) at the origin of the disease. This maybe the only way to identify rare cell types, such as cancer stem cells and circulating tumour cells, and therefore better characterize mechanisms of resistance to treatments, and of tumour reoccurrence. In stem cell research, characterisation of differentiation pathways is a central question to improve disease modelling and drug screening assays, and ultimately for regenerative medicine. Pseudo-time analyses have already provided invaluable information, for example in pancreatic islets, to improve protocols for b-cells differentiation. Most endocrine organs have now been examined using sc RNAseq, revealing novel information about known cell types, and also new cellular subpopulations.