A Broad Overview of Computational Methods for Predicting the Pathophysiological Effects of Non-synonymous Variants.
Next-generation sequencing has provided extraordinary opportunities to investigate the massive human genetic variability. It helped identifying several kinds of genomic mismatches from the wild-type reference genome sequences and to explain the onset of several pathogenic phenotypes and diseases susceptibility. In this context, distinguishing pathogenic from functionally neutral amino acid changes turns out to be a task as useful as complex, expensive, and time-consuming.Here, we present an exhaustive and up-to-dated survey of the algorithms and software packages conceived for the estimation of the putative pathogenicity of mutations, along with a description of the most popular mutation datasets that these tools used as training sets. Finally, we present and describe software for the prediction of cancer-related mutations.
IRCCS Casa Sollievo della Sofferenza, Viale Cappuccini 1, 71013, San Giovanni Rotondo (FG), Italy.
Stefano
S
Castellana
IRCCS Casa Sollievo della Sofferenza, Viale Regina Margherita 261, 00198, Rome, Italy.
Caterina
C
Fusilli
IRCCS Casa Sollievo della Sofferenza, Viale Regina Margherita 261, 00198, Rome, Italy. t.mazza@css-mendel.it.
Tommaso
T
Mazza
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D064878:Web Browser
Genomic mutations; Next-generation sequencing; Pathogenicity prediction; Whole exome sequencing