Single Nucleotide Variant Detection Using Next Generation Sequencing

摘要: Single nucleotide variants (SNVs) occur when a single (e.g., A, T, C, or G) is altered in the DNA sequence. SNVs are by far most common type of sequence change, and there number endogenous exogenous sources damage that lead to base pair substitution mutations create SNVs. The biologic impact coding regions depends on their (synonymous versus missense), noncoding RNA processing gene regulation. Nonetheless, selection pressure reduces overall frequency substitutions associated regulatory sequences, with result SNV rate much less than DNA. utility clinical next generation sequencing (NGS) assay designed detect design features including an amplification-based hybrid capture-based targeted approach, library complexity, depth sequencing, tumor cellularity (in cancer specimens), specimen fixation, platform. From bioinformatic perspective, many popular NGS analysis programs for detection constitutional genome where either 50% (heterozygous) 100% (homozygous) reads; these prior probabilities often built-in algorithms, consequently variant allele frequencies (VAFs) falling too outside expected range homozygous heterozygous ignored as false positives. Thus, sensitive specific approaches acquired require significant revision software packages testing new algorithms altogether. Some tools optimized very data, but high coverage acceptable performance rely spike-in control samples order calibrate run-dependent error models, must be accounted design. There online can used predict evaluate whether has documented disease association. Guidelines reporting detected have been developed; consensus guidelines somatic under development.