IIGM/CSP, Armenise-Harvard foundation, AIRC IG 2020 ID 24463; Ministero della Salute ‘COVID-2020-12371849’, FPO/Candiolo Advance 5×1000_2018 ‘Im-MEMORY’; Ministero della Salute Ricerca Corrente 2021.University of Bologna. Department of Biological, Geological and Environmental Sciences. Laboratory of Molecular Anthropology. Center for Genome Biology. Bologna, Italy / Italian Institute for Genomic Medicine. Armenise-Harvard Immune Regulation Unit. Turin, ItalyItalian Institute for Genomic Medicine. Armenise-Harvard Immune Regulation Unit. Turin, Italy / Fondazione del Piemonte per l'Oncologia. Candiolo Cancer Institute. Candiolo, Turin, ItalyMinistério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, BrasilItalian Institute for Genomic Medicine. Armenise-Harvard Immune Regulation Unit. Turin, Italy / Fondazione del Piemonte per l'Oncologia. Candiolo Cancer Institute. Candiolo, Turin, ItalySingle-cell multi-omics is a rapidly evolving field, thanks to a fast technological improvement and the growing accuracy of dedicated computational tools for data analysis. Its importance is highlighted by the possibility to distinguish apparently identical cells based on their pattern of gene expression. In this review, the mostly used methodological pipelines for single-cell analysis, as well as the advantages and potential limitations of several analytical steps, are presented and discussed, with specific sections focusing on crucial parts of this procedure, their bioinformatic tools, as well as their advantages and potential drawbacks. The current bioinformatic approaches for T-cell receptor (TCR) reconstruction are also introduced, as well as a comparison of single-cell sequencing technologies. Critical points that may introduce analytical biases and potential inaccuracies in data interpretation are also highlighted
