Computational Resources for the Interpretation of Variations in Cancer

Grete Francesca Privitera; Salvatore Alaimo; Alfredo Ferro; Alfredo Pulvirenti

doi:10.1007/978-3-030-91836-1_10

Computational Resources for the Interpretation of Variations in Cancer

Adv Exp Med Biol. 2022:1361:177-198. doi: 10.1007/978-3-030-91836-1_10.

Authors

Grete Francesca Privitera^{1

2}, Salvatore Alaimo², Alfredo Ferro², Alfredo Pulvirenti³

Affiliations

¹ Department of Physics and Astronomy, University of Catania, Catania, Italy.
² Department of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy.
³ Department of Clinical and Experimental Medicine, Bioinformatics Unit, University of Catania, Catania, Italy. alfredo.pulvirenti@unict.it.

PMID: 35230689
DOI: 10.1007/978-3-030-91836-1_10

Abstract

A broad ecosystem of resources, databases, and systems to analyze cancer variations is present in the literature. These are a strategic element in the interpretation of NGS experiments. However, the intrinsic wealth of data from RNA-seq, ChipSeq, and DNA-seq can be fully exploited only with the proper skill and knowledge. In this chapter, we survey relevant literature concerning databases, annotators, and variant prioritization tools.

Keywords: DNA alterations; DNA-Seq; Mutations; NGS; RNA-Seq; Variant annotation; Variant databases; Variant interpretation; Variant pathogenicity assessment; Variant prioritization.

MeSH terms

Computational Biology
DNA
Ecosystem*
Exome Sequencing
High-Throughput Nucleotide Sequencing
Humans
Neoplasms* / genetics
Software

Substances

DNA