Bioinformatics Basics for High-Throughput Hybridization-Based Targeted DNA Sequencing from FFPE-Derived Tumor Specimens: From Reads to Variants.

The use of next-generation sequencing and hybridization-based capture for target enrichment have enabled the interrogation of coding regions of several clinically significant cancer genes in tumor specimens using both targeted panels of a few to hundreds of genes, to whole-exome panels encompassing coding regions of all genes in the genome. Next-generation sequencing (NGS) technologies produce millions of relatively short segments of sequences or reads that require bioinformatics tools to map reads back to a reference genome using various read alignment tools, as well as to determine differences between single bases (single nucleotide variants or SNVs) or multiple bases (insertions and deletions or indels) between the aligned reads and the reference genome to call variants. In addition to single nucleotide changes or small insertions and deletions, high copy gains and losses can also be gleaned from NGS data to call gene amplifications and deletions. Throughout these processes, numerous quality control metrics can be assessed at each step to ensure that the resulting called variants are of high quality and are accurate. In this chapter we review common tools used to generate reads from Illumina-derived sequence data, align reads, and call variants from hybridization-based targeted NGS panel data generated from tumor FFPE-derived DNA specimens as well as basic quality metrics to assess for each assayed specimen.