StrainSeeker: fast identification of bacterial strains from raw sequencing reads using user-provided guide trees

PeerJ

article

Märt Roosaare¹  Mihkel Vaher¹  Lauris Kaplinski¹  Märt Möls¹  Reidar Andreson¹  Maarja Lepamets¹  Triinu Kõressaar¹  Paul Naaber³  Siiri Kõljalg⁴  Maido Remm¹ 

[1] Department of Bioinformatics, University of Tartu;Institute of Mathematical Statistics, University of Tartu;Synlab Eesti;Department of Microbiology, Institute of Biomedicine and Translational Medicine, University of Tartu;United Laboratories, Tartu University Clinics

关键词: k-mer;    Clade;    Strain identification;    Species identification;    Diagnostics;   

DOI  :  10.7717/peerj.3353

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Background Fast, accurate and high-throughput identification of bacterial isolates is in great demand. The present work was conducted to investigate the possibility of identifying isolates from unassembled next-generation sequencing reads using custom-made guide trees. Results A tool named StrainSeeker was developed that constructs a list of specific k-mers for each node of any given Newick-format tree and enables the identification of bacterial isolates in 1–2 min. It uses a novel algorithm, which analyses the observed and expected fractions of node-specific k-mers to test the presence of each node in the sample. This allows StrainSeeker to determine where the isolate branches off the guide tree and assign it to a clade whereas other tools assign each read to a reference genome. Using a dataset of 100 Escherichia coli isolates, we demonstrate that StrainSeeker can predict the clades of E. coli with 92% accuracy and correct tree branch assignment with 98% accuracy. Twenty-five thousand Illumina HiSeq reads are sufficient for identification of the strain. Conclusion StrainSeeker is a software program that identifies bacterial isolates by assigning them to nodes or leaves of a custom-made guide tree. StrainSeeker’s web interface and pre-computed guide trees are available at http://bioinfo.ut.ee/strainseeker. Source code is stored at GitHub: https://github.com/bioinfo-ut/StrainSeeker.

【 授权许可】

CC BY