Rapid identification of non-human sequences in high-throughput sequencing datasets

Abstract

Rapid identification of non-human sequences (RINS) is an intersection-based pathogen detection workflow that utilizes a user-provided custom reference genome set for identification of non-human sequences in deep sequencing datasets. In <2 h, RINS correctly identified the known virus in the dataset SRR73726 and is compatible with any computer capable of running the prerequisite alignment and assembly programs. RINS accurately identifies sequencing reads from intact or mutated non-human genomes in a dataset and robustly generates contigs with these non-human sequences (Supplementary Material).

Availability: RINS is available for free download at http://khavarilab.stanford.edu/resources.html.

Fig. 1.

RINS uses intersection (marked by asterisks), not subtraction, to identify non-human reads. The workflow intersects the reads in the dataset with a reference of non-human genomes of interest using Blat to align non-overlapping 25 mers for each read. Reads with >80% homology are aligned to the human genome and reads with >97% homology are removed from the read set. Remaining reads are complexity filtered with an LZW compression ratio of 0.50 and mate pairs for sufficiently complex reads are identified. This read set is then assembled into pathogen sequence contigs.