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Efficient and Robust Search of Microbial Genomes via Phylogenetic Compression.

Karel Bå IndaLeandro LimaSimone PignottiNatalia Quinones-OlveraKamil SalikhovRayan ChikhiGregory KucherovZamin IqbalMichael H Baym
Published in: bioRxiv : the preprint server for biology (2023)
Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections makes it effectively impossible to search these data using tools such as BLAST and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. We show that, when applied to modern diverse collections approaching millions of genomes, lossless phylogenetic compression improves the compression ratios of assemblies, de Bruijn graphs, and k -mer indexes by one to two orders of magnitude. Additionally, we develop a pipeline for a BLAST-like search over these phylogeny-compressed reference data, and demonstrate it can align genes, plasmids, or entire sequencing experiments against all sequenced bacteria until 2019 on ordinary desktop computers within a few hours. Phylogenetic compression has broad applications in computational biology and may provide a fundamental design principle for future genomics infrastructure.
Keyphrases
  • electronic health record
  • microbial community
  • big data
  • machine learning
  • single cell
  • high resolution
  • genome wide
  • artificial intelligence
  • transcription factor
  • current status