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Genome Biol. 2013 Mar 13;14(3):R23. doi: 10.1186/gb-2013-14-3-r23.

DDIG-in: discriminating between disease-associated and neutral non-frameshifting micro-indels.

Abstract

Micro-indels (insertions or deletions shorter than 21 bps) constitute the second most frequent class of human gene mutation after single nucleotide variants. Despite the relative abundance of non-frameshifting indels, their damaging effect on protein structure and function has gone largely unstudied. We have developed a support vector machine-based method named DDIG-in (Detecting disease-causing genetic variations due to indels) to prioritize non-frameshifting indels by comparing disease-associated mutations with putatively neutral mutations from the 1,000 Genomes Project. The final model gives good discrimination for indels and is robust against annotation errors. A webserver implementing DDIG-in is available at http://sparks-lab.org/ddig.

PMID:
23497682
[PubMed - in process]
PMCID:
PMC4053752
Free PMC Article

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