TarSeqQC: Quality Control on Targeted Sequencing Experiments in R

ABSTRACT

Targeted sequencing is growing as a screening methodology used in research and medical genetics to identify genomic alterations causing human diseases. In general, a list of possible genomic variants is derived from mapped reads through a variant calling step. This processing step is usually based on variant coverage, although it may be affected by several factors. Therefore, under-covered relevant clinical variants may not be reported, impacting on pathology diagnosis or treatment. Thus, a prior quality control of the experiment is critical to determine variant detection accuracy and to avoid erroneous medical conclusions. There are several quality control tools, but they are focused on issues related to whole genome sequencing. However, in targeted sequencing, quality control should assess experiment, gene and genomic region performances based on achieved coverages.

Here, we propose TarSeqQC R package for quality control in targeted sequencing experiments. The tool is freely available at Bioconductor repository. TarSeqQC was used to analyze two datasets; low-performance primer pools and features were detected, enhancing the quality of experiment results. Read count profiles were also explored, showing TarSeqQC's effectiveness as an exploration tool. Our proposal may be a valuable bioinformatic tool for routinely targeted sequencing experiments in both research and medical genetics.

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