Identifying genetic variations is important to understand complex human disease. Among these variations, insertion and deletion (InDel) polymorphisms are less discovered rather than single nucleotide polymorphisms (SNPs). The common approaches for InDel detection utilize the computational analysis on re-tracing data. However, most of these methods still required human inspection to decrease false positives. We proposed a novel algorithm to capture his pattern with the IUPAC alphabet using a hidden Markov model (HMM).
Mutation Explorer supports GUI to read Sanger sequencing traces. It marks possible InDel region.