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bioRxiv · 10.1101/2022.05.05.487569

Systematic benchmarking of all-in-one microbial SNP calling pipelines

Falconer, C.·Cuddihy, T.·Beatson, S.·Paterson, D.·Harris, P.·Forde, B.
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Abstract

Clinical and public health microbiology is increasingly utilising whole genome sequencing (WGS) technology and this has lead to the development of a myriad of analysis tools and bioinformatics pipelines. Single nucleotide polymorphism (SNP) analysis is an approach used for strain characterisation and determining isolate relatedness. However, in order to ensure the development of robust methodologies suitable for clinical application of this technology, accurate, reproducible, traceable and benchmarked analysis pipelines are necessary. To date, the approach to benchmarking of these has been largely ad-hoc with new pipelines benchmarked on their own datasets with limited comparisons to previously published pipelines. In this study, Snpdragon, a fast and accurate SNP calling pipeline is introduced. Written in Nextflow, Snpdragon is capable of handling small to very large and incrementally growing datasets. Snpdragon is benchmarked using previously published datasets against six other all-in-one microbial SNP calling pipelines, Lyveset, Lyveset2, Snippy, SPANDx, BactSNP and Nesoni. The effect of dataset choice on performance measures is demonstrated to highlight some of the issues associated with the current available benchmarking approaches. The establishment of an agreed upon gold-standard benchmarking process for microbial variant analysis is becoming increasingly important to aid in its robust application, improve transparency of pipeline performance under different settings and direct future improvements and development. Snpdragon is available at https://github.com/FordeGenomics/SNPdragon. Impact statementWhole-genome sequencing has become increasingly popular in infectious disease diagnostics and surveillance. The resolution provided by single nucleotide polymorphism (SNP) analyses provides the highest level of insight into strain characteristics and relatedness. Numerous approaches to SNP analysis have been developed but with no established gold-standard benchmarking approach, choice of bioinformatics pipeline tends to come down to laboratory or researcher preference. To support the clinical application of this technology, accurate, transparent, auditable, reproducible and benchmarked pipelines are necessary. Therefore, Snpdragon has been developed in Nextflow to allow transparency, auditability and reproducibility and has been benchmarked against six other all-in-one pipelines using a number of previously published benchmarking datasets. The variability of performance measures across different datasets is shown and illustrates the need for a robust, fair and uniform approach to benchmarking. Data SummaryO_LIPreviously sequenced reads for Escherichia coli O25b:H4-ST131 strain EC958 are available in BioProject PRJNA362676. BioSample accession numbers for the three benchmarking isolates are: O_LIEC958: SAMN06245884 C_LIO_LIMS6573: SAMN06245879 C_LIO_LIMS6574: SAMN06245880 C_LI C_LIO_LIAccession numbers for reference genomes against the E. coli O25b:H4-ST131 strain EC958 benchmark are detailed in table 2. C_LIO_LISimulated benchmarking data previously described by Yoshimura et al. is available at http://platanus.bio.titech.ac.jp/bactsnp (1). C_LIO_LISimulated datasets previously described by Bush et al. is available at http://dx.doi.org/10.5287/bodleian:AmNXrjYN8 (2). C_LIO_LIReal sequencing benchmarking datasets previously described by Bush et al. are available at http://dx.doi.org/10.5287/bodleian:nrmv8k5r8 (2). C_LI O_TBL View this table: org.highwire.dtl.DTLVardef@f2446corg.highwire.dtl.DTLVardef@16a299corg.highwire.dtl.DTLVardef@d1c7a5org.highwire.dtl.DTLVardef@8a3cbaorg.highwire.dtl.DTLVardef@198f455_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONReference genomes used in the EC958 benchmarking dataset and the percent identity against the three included samples. C_TABLECAPTION C_TBL

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Falconer, C., Cuddihy, T., Beatson, S., Paterson, D., Harris, P., Forde, B.. 2022-05-06. Systematic benchmarking of all-in-one microbial SNP calling pipelines. https://doi.org/10.1101/2022.05.05.487569

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