Jixiang Liu
Quanxue Li
Wei Liu
Yi-Xue Li
Yuan-Yuan Li
aShanghai Center for Bioinformation Technology, Shanghai 201203, China
bShanghai Engineering Research Center of Pharmaceutical Translation & Shanghai Industrial Technology Institute, Shanghai 201203, China
cSchool of Biotechnology, East China University of Science and Technology, Shanghai 200237, China
dShanghai Industrial Technology Institute, Shanghai 201203, China
More InformationCorresponding author: E-mail address: yxli@scbit.org (Yi-Xue Li);E-mail address: yyli@scbit.org (Yuan-Yuan Li)
Received Date: 2018-01-08
Accepted Date:2018-07-09
Rev Recd Date:2018-06-15
Available Online: 2018-07-25 Publish Date:2018-07-20
Abstract
Abstract
The application of next-generation sequencing (NGS) technology in cancer is influenced by the quality and purity of tissue samples. This issue is especially critical for patient-derived xenograft (PDX) models, which have proven to be by far the best preclinical tool for investigating human tumor biology, because the sensitivity and specificity of NGS analysis in xenograft samples would be compromised by the contamination of mouse DNA and RNA. This definitely affects downstream analyses by causing inaccurate mutation calling and gene expression estimates. The reliability of NGS data analysis for cancer xenograft samples is therefore highly dependent on whether the sequencing reads derived from the xenograft could be distinguished from those originated from the host. That is, each sequence read needs to be accurately assigned to its original species. Here, we review currently available methodologies in this field, including Xenome, Disambiguate, bamcmp and pdxBlacklist, and provide guidelines for users.Keywords: Patient-derived xenograft,
Next-generation sequencing,
Host contamination control,
Alignment
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