henhaobio
Sign in

BioinformaticsBioinformaticsPeer-reviewed journal article

Parsnp 2.0: Scalable Core-Genome Alignment for Massive Microbial Datasets

Bryce L. KilleiD, Michael NuteiD, Victor Huang, Eddie KimiD, Adam M. PhillippyiD, Todd J. TreangeniD

PDFDOIPreprintCode

Abstract

MotivationSince 2016, the number of microbial species with available reference genomes in NCBI has more than tripled. Multiple genome alignment, the process of identifying nucleotides across multiple genomes which share a common ancestor, is used as the input to numerous downstream comparative analysis methods. Parsnp is one of the few multiple genome alignment methods able to scale to the current era of genomic data; however, there has been no major release since its initial release in 2014. ResultsTo address this gap, we developed Parsnp v2, which significantly improves on its original release. Parsnp v2 provides users with more control over executions of the program, allowing Parsnp to be better tailored for different use-cases. We introduce a partitioning option to Parsnp, which allows the input to be broken up into multiple parallel alignment processes which are then combined into a final alignment. The partitioning option can reduce memory usage by over 4x and reduce runtime by over 2x, all while maintaining a precise core-genome alignment. The partitioning workflow is also less susceptible to complications caused by assembly artifacts and minor variation, as alignment anchors only need to be conserved within their partition and not across the entire input set. We highlight the performance on datasets involving thousands of bacterial and viral genomes. AvailabilityParsnp is available at https://github.com/marbl/parsnp

Citations
112
FWCI
15.20
Field percentile
top 1%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISTreangen '14Gulhan '25Chandra '26Wachsmann '26Hennig '19Al‐Ghalith '20
70% semantic matchBioinformatics
Todd J. Treangen, Brian D. Ondov, Sergey Koren+1 more·bioRxiv·Oct 20, 2014