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Exome-assistant: a rapid and easy detection of disease-related genes and genetic variations from exome sequencing

Qi Liu1, Enjian Shen1, Qingjie Min1, Xueying Li1, Xin Wang1, Xianfeng Li1, Zhong Sheng Sun12* and Jinyu Wu1*

Author affiliations

1 Institute of Genomic Medicine, Wenzhou Medical College, Wenzhou 325035, China

2 Beijing Institutes for Biological Sciences, Chinese Academy of Science, Beijing 100101, China

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Citation and License

BMC Genomics 2012, 13:692  doi:10.1186/1471-2164-13-692

Published: 11 December 2012



Protein-coding regions in human genes harbor 85% of the mutations that are associated with disease-related traits. Compared with whole-genome sequencing of complex samples, exome sequencing serves as an alternative option because of its dramatically reduced cost. In fact, exome sequencing has been successfully applied to identify the cause of several Mendelian disorders, such as Miller and Schinzel-Giedio syndrome. However, there remain great challenges in handling the huge data generated by exome sequencing and in identifying potential disease-related genetic variations.


In this study, Exome-assistant ( webcite), a convenient tool for submitting and annotating single nucleotide polymorphisms (SNPs) and insertion/deletion variations (InDels), was developed to rapidly detect candidate disease-related genetic variations from exome sequencing projects. Versatile filter criteria are provided by Exome-assistant to meet different users’ requirements. Exome-assistant consists of four modules: the single case module, the two cases module, the multiple cases module, and the reanalysis module. The two cases and multiple cases modules allow users to identify sample-specific and common variations. The multiple cases module also supports family-based studies and Mendelian filtering. The identified candidate disease-related genetic variations can be annotated according to their sample features.


In summary, by exploring exome sequencing data, Exome-assistant can provide researchers with detailed biological insights into genetic variation events and permits the identification of potential genetic causes of human diseases and related traits.

Next generation sequencing; Mendelian disease; Single nucleotide polymorphisms; Insertions and deletions; Variation filtering; Minor allele frequency