Sequencing quality assessment tools to enable data-driven informatics for high throughput genomics

Abstract

The processes of quality assessment and control are an active area of research at The Genome Analysis Centre (TGAC). Unlike other sequencing centers that often concentrate on a certain species or technology, TGAC applies expertise in genomics and bioinformatics to a wide range of projects, often requiring bespoke wet lab and in silico workflows. TGAC is fortunate to have access to a diverse range of sequencing and analysis platforms, and we are at the forefront of investigations into library quality and sequence data assessment. We have developed and implemented a number of algorithms, tools, pipelines and packages to ascertain, store, and expose quality metrics across a number of next-generation sequencing platforms, allowing rapid and in-depth cross-platform Quality Control (QC) bioinformatics. In this review, we describe these tools as a vehicle for data-driven informatics, offering the potential to provide richer context for downstream analysis and to inform experimental design.

Keywords: NGS data analysis; QC; bioinformatics tools; contamination screening; quality assessment and improvement; quality control; run statistics; sequence analysis.

Figure 1

Data flow through the Primary Analysis Pipeline, focused on the Illumina platform.

Figure 2

Example kmer spectra. An initial peak around coverage 1 is indicative of sequencing errors. Two further peaks indicate heterozygosity.