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Fast Lightweight Accurate Xenograft Sorting

Authors Jens Zentgraf , Sven Rahmann



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LIPIcs.WABI.2020.4.pdf
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Jens Zentgraf
  • Bioinformatics, Computer Science XI, TU Dortmund University, Germany
Sven Rahmann
  • Genome Informatics, Institute of Human Genetics, University of Duisburg-Essen, Essen, Germany

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Jens Zentgraf and Sven Rahmann. Fast Lightweight Accurate Xenograft Sorting. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 4:1-4:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.WABI.2020.4

Abstract

Motivation: With an increasing number of patient-derived xenograft (PDX) models being created and subsequently sequenced to study tumor heterogeneity and to guide therapy decisions, there is a similarly increasing need for methods to separate reads originating from the graft (human) tumor and reads originating from the host species' (mouse) surrounding tissue. Two kinds of methods are in use: On the one hand, alignment-based tools require that reads are mapped and aligned (by an external mapper/aligner) to the host and graft genomes separately first; the tool itself then processes the resulting alignments and quality metrics (typically BAM files) to assign each read or read pair. On the other hand, alignment-free tools work directly on the raw read data (typically FASTQ files). Recent studies compare different approaches and tools, with varying results. Results: We show that alignment-free methods for xenograft sorting are superior concerning CPU time usage and equivalent in accuracy. We improve upon the state of the art by presenting a fast lightweight approach based on three-way bucketed quotiented Cuckoo hashing. Our hash table requires memory comparable to an FM index typically used for read alignment and less than other alignment-free approaches. It allows extremely fast lookups and uses less CPU time than other alignment-free methods and alignment-based methods at similar accuracy.

Subject Classification

ACM Subject Classification
  • Applied computing → Molecular sequence analysis
  • Applied computing → Bioinformatics
  • Theory of computation → Bloom filters and hashing
  • Theory of computation → Data structures design and analysis
Keywords
  • xenograft sorting
  • alignment-free method
  • Cuckoo hashing
  • k-mer

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