Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

By Ben Langmead, Cole Trapnell, Mihai Pop, Steven L. Salzberg. Genome Biology, 2009

22,181 citations recorded by the source corpus.

Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source http://bowtie.cbcb.umd.edu.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ebe875cf08dd398e0ed25f518502301c984a9afe

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Citations in the corpus

CCTop: An Intuitive, Flexible and Reliable CRISPR/Cas9 Target Prediction Tool (2015, methodology): “The search of off-target sites is carried out using Bowtie [18] version 0.12.7.”
Architectural protein subclasses shape 3D organization of genomes during lineage commitment. (2013, positive): “All ChIP-seq data sets were aligned to build version MM9 of the mouse genome using default parameters (-v1 -m1) in Bowtie version 0.12.2 (Langmead et al., 2009).”
Metabolic Induction of Trained Immunity through the Mevalonate Pathway. (2018, neutral): “2 Beckman Coulter N/A NanoDrop software N/A GraphPad Prism Graphpad Software https://www.graphpad.com Bowtie 1 Langmead et al., 2009 http://bowtie-bio.sourceforge.net/index.shtml MMSEQ Turro et al., 2011 https://github.com/eturro/mmseq DEseq Anders and Huber 2010…”
The stress granule transcriptome reveals principles of mRNA accumulation in stress granules (2017, neutral): “An index genome was built with Bowtie 0.12.7 using the ‘build’ command and the S288C reference genome version (R64-1-1), which was acquired through Saccharomyces Genome Database (SGD)(Langmead et al., 2009).”
Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM) (2011, methodology): “RNA-Seq data are discrete in nature; therefore, with reasonable gene models and comparative metrics RNA-Seq data can be simulated to sufficient accuracy to enable meaningful benchmarking of alignment algorithms.”
Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory (2012, methodology): “The relationship between many existing alignment methods [1,3-5,10-23] is qualitatively illustrated in Figure 1.”