AirLift remaps read alignments between similar reference genomes up to 27.4x faster than full re-mapping while maintaining high accuracy for SNP and INDEL variant calling as validated with GATK.
Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human. It automatically chooses between local and end-to-end alignments, supports paired-end reads and performs chimeric alignment. The algorithm is robust to sequencing errors and applicable to a wide range of sequence lengths from 70bp to a few megabases. For mapping 100bp sequences, BWA-MEM shows better performance than several state-of-art read aligners to date. Availability and implementation: BWA-MEM is implemented as a component of BWA, which is available at http://github.com/lh3/bwa. Contact: hengli@broadinstitute.org
representative citing papers
Parse indexing supplies lower bounds on longest MEM lengths inside pseudo-MEMs, enabling safe discarding of short ones during KeBaB preprocessing.
citing papers explorer
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AirLift: A Fast and Comprehensive Technique for Remapping Alignments between Reference Genomes
AirLift remaps read alignments between similar reference genomes up to 27.4x faster than full re-mapping while maintaining high accuracy for SNP and INDEL variant calling as validated with GATK.
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Parse indexing for discarding short pseudo-MEMs safely
Parse indexing supplies lower bounds on longest MEM lengths inside pseudo-MEMs, enabling safe discarding of short ones during KeBaB preprocessing.