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SIFT Indel: Predictions for the Functional Effects of Amino Acid Insertions/Deletions in Proteins
Authors:Jing Hu  Pauline C. Ng
Affiliation:1. Department of Mathematics and Computer Science, Franklin and Marshall College, Lancaster, Pennsylvania, United States of America.; 2. Department of Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore .; Ohio State University Medical Center, United States of America,
Abstract:Indels in the coding regions of a gene can either cause frameshifts or amino acid insertions/deletions. Frameshifting indels are indels that have a length that is not divisible by 3 and subsequently cause frameshifts. Indels that have a length divisible by 3 cause amino acid insertions/deletions or block substitutions; we call these 3n indels. The new amino acid changes resulting from 3n indels could potentially affect protein function. Therefore, we construct a SIFT Indel prediction algorithm for 3n indels which achieves 82% accuracy, 81% sensitivity, 82% specificity, 82% precision, 0.63 MCC, and 0.87 AUC by 10-fold cross-validation. We have previously published a prediction algorithm for frameshifting indels. The rules for the prediction of 3n indels are different from the rules for the prediction of frameshifting indels and reflect the biological differences of these two different types of variations. SIFT Indel was applied to human 3n indels from the 1000 Genomes Project and the Exome Sequencing Project. We found that common variants are less likely to be deleterious than rare variants. The SIFT indel prediction algorithm for 3n indels is available at http://sift-dna.org/
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