Abstract
Next generation sequencing technology has revolutionized the study of cancers. Through matched normal-tumor pairs, it is now possible to identify genome-wide germline and somatic mutations. The generation and analysis of the data requires rigorous quality checks and filtering, and the current analytical pipeline is constantly undergoing improvements. We noted however that in analyzing matched pairs, there is an implicit assumption that the sequenced data are matched, without any quality check such as those implemented in association studies. There are serious implications in this assumption as identification of germline and rare somatic variants depend on the normal sample being the matched pair. Using a genetics concept on measuring relatedness between individuals, we demonstrate that the matchedness of tumor pairs can be quantified and should be included as part of a quality protocol in analysis of sequenced data. Despite the mutation changes in cancer samples, matched tumor-normal pairs are still relatively similar in sequence compared to non-matched pairs. We demonstrate that the approach can be used to assess the mutation landscape between individuals.
Highlights
Mutations are hallmark of cancers and identification of the mutations is imperative in our understanding of the disease
Two datasets were used in the study; 82 matched pairs on SNP6 and 7 pairs sequenced using next generation sequencing (NGS)
Five matched pairs were common in SNP6 and NGS
Summary
Mutations are hallmark of cancers and identification of the mutations is imperative in our understanding of the disease. The technology offers a powerful and yet relatively cost effective approach to characterize genome-wide mutations that occur in diseases. It enables identification of somatic mutations, including base substitutions, indels, chromosomal rearrangements, copy number alterations, and transcriptional aberrations. While the approach in NGS has been rigorous in the generation of data as well as analysis, we note that there is a lack of quality check to assess if the matched normal-tumor pair was matched. Since identification of germline and de novo rare somatic mutations relies on the matched normal sample, there is necessity to perform quality check on the sequenced data, to ensure the basis of the assumption is upheld. It is timely to consider relatedness checks and incorporate it as a quality control protocol for NGS analysis
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