Zhao, Huiying, Yang, Yuedong, Lin, Hai, Zhang, Xinjun, Mort, Matthew, Cooper, David Neil ORCID: https://orcid.org/0000-0002-8943-8484, Liu, Yunlong and Zhou, Yaoqi 2013. DDIG-in: discriminating between disease-associated and neutral non-frameshifting micro-indels. Genome Biology 14 (3) , R23. 10.1186/gb-2013-14-3-r23. |
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.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Medicine |
Subjects: | R Medicine > RZ Other systems of medicine |
Publisher: | BioMed Central |
ISSN: | 1465-6906 |
Last Modified: | 17 Jun 2023 19:36 |
URI: | https://orca.cardiff.ac.uk/id/eprint/84048 |
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