Abstract
Single-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.
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