title: 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.
authors.forename: Huiying
authors.initials: H
authors.lastname: Zhao
authors.forename: Yuedong
authors.initials: Y
authors.lastname: Yang
authors.forename: Hai
authors.initials: H
authors.lastname: Lin
authors.forename: Xinjun
authors.initials: X
authors.lastname: Zhang
authors.forename: Matthew
authors.initials: M
authors.lastname: Mort
authors.forename: David N
authors.initials: DN
authors.lastname: Cooper
authors.forename: Yunlong
authors.initials: Y
authors.lastname: Liu
authors.forename: Yaoqi
authors.initials: Y
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D017124:Conserved Sequence / Q000235:genetics; D004247:DNA / Q000235:genetics; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics*; D016368:Frameshift Mutation / Q000235:genetics*; D005787:Gene Frequency / Q000235:genetics; D006801:Humans; D054643:INDEL Mutation / Q000235:genetics*; D012372:ROC Curve; D012689:Sequence Homology, Nucleic Acid; D060388:Support Vector Machine
chemical_list: D004247:DNA