SeqPurge: highly-sensitive adapter trimming for paired-end short read data

Trimming adapter sequences from short read data is a common preprocessing step in most DNA/RNA sequence analysis pipelines. For amplicon-based approaches, which are mostly used in clinical diagnostics, sensitive adapter trimming is of special importance. Untrimmed adapters can be located at the same genomic position and can lead to spurious variant calls. Shotgun approaches are more robust towards adapter contamination, because untrimmed adapters are randomly distributed over the target region. This reduces the probability of spurious variant calls. When performing paired-end sequencing, the overlap between forward and reverse read can be used to identify excess adapter sequences. This is exploited by several published adapter trimming tools. However, in our evaluations on amplicon-based paired-end data we found that these tools fail to remove all adapter sequences and that adapter contamination leads to spurious variant calls. Here we present SeqPurge, a highly-sensitive adapter trimmer that uses a probabilistic approach to detect the overlap between forward and reverse reads of paired-end Illumina sequencing data. The overlap information is then used to remove adapter sequences, even if only one base long. Compared to other adapter trimmers specifically designed for paired-end data, we found that SeqPurge achieves a higher sensitivity. The number of remaining adapters after trimming is reduced by 40-75%, depending on the compared tool. The specificity of SeqPurge is comparable to that of the compared tools. In addition to adapter trimming, SeqPurge can also perform trimming based on quality and based on no-call (N) stretches. SeqPurge is available as part of the ngs-bits project at GitHub:  https://github.com/marc-sturm/ngs-bits