SiNVICT: ultra-sensitive detection of single nucleotide variants and indels in circulating tumour DNA

Motivation: Successful development and application of precision oncology approaches require robust elucidation of the genomic landscape of a patient’s cancer and, ideally, the ability to monitor therapy-induced genomic changes in the tumour in an inexpensive and minimally invasive manner. Thanks to recent advances in sequencing technologies, ‘liquid biopsy’, the sampling of patient’s bodily fluids such as blood and urine, is considered as one of the most promising approaches to achieve this goal. In many cancer patients, and especially those with advanced metastatic disease, deep sequencing of circulating cell free DNA (cfDNA) obtained from patient’s blood yields a mixture of reads originating from the normal DNA and from multiple tumour subclones—called circulating tumour DNA or ctDNA. The ctDNA/cfDNA ratio as well as the proportion of ctDNA originating from specific tumour subclones depend on multiple factors, making comprehensive detection of mutations difficult, especially at early stages of cancer. Furthermore, sensitive and accurate detection of single nucleotide variants (SNVs) and indels from cfDNA is constrained by several factors such as the sequencing errors and PCR artifacts, and mapping errors related to repeat regions within the genome. In this article, we introduce SiNVICT, a computational method that increases the sensitivity and specificity of SNV and indel detection at very low variant allele frequencies. SiNVICT has the c...
Source: Bioinformatics - Category: Bioinformatics Authors: Tags: SEQUENCE ANALYSIS Source Type: research