Proteogenomics: concepts, applications, and computational strategies

By Alexey I. Nesvizhskii. Nature Methods, 2014

687 citations recorded by the source corpus.

Proteogenomics is an area of research at the interface of proteomics and genomics. In this approach, customized protein sequence databases generated using genomic and transcriptomic information are used to help identify novel peptides (not present in reference protein sequence databases) from mass spectrometry–based proteomic data; in turn, the proteomic data can be used to provide protein-level evidence of gene expression and to help refine gene models. In recent years, owing to the emergence of new sequencing technologies such as RNA-seq and dramatic improvements in the depth and throughput of mass spectrometry–based proteomics, the pace of proteogenomic research has greatly accelerated. Here I review the current state of proteogenomic methods and applications, including computational strategies for building and using customized protein sequence databases. I also draw attention to the challenge of false positive identifications in proteogenomics and provide guidelines for analyzing the data and reporting the results of proteogenomic studies.

View Paper: https://www.semanticscholar.org/paper/8cdd128e5b86cb42cf42885808c445e8fe55d131

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Citations in the corpus

• SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation (2017, background): “down the search space and increase the statistical power for identifying the correct peptide-spectrum matches [18, 53].”