bowtie2
TLDR
Align reads to a reference genome
SYNOPSIS
bowtie2 [options] -x index {-1 m1 -2 m2 | -U reads} -S sam
bowtie2-build [options] reference indexbase_
DESCRIPTION
bowtie2 is a fast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 to 1000 base pairs to relatively large genomes like the human genome.
Bowtie2 uses an FM Index (based on the Burrows-Wheeler transform) for the reference genome, enabling fast alignment while maintaining low memory usage. It supports gapped, local, and paired-end alignment modes.
The alignment output is SAM format, which can be processed by samtools and other downstream tools for variant calling, expression analysis, and other genomics workflows.
PARAMETERS
-x index
Index filename prefix (built with bowtie2-build).-1 reads
Comma-separated files with #1 mates.-2 reads
Comma-separated files with #2 mates.-U reads
Comma-separated files with unpaired reads.-S sam
Output SAM file.-p threads
Number of parallel threads.--local
Local alignment mode (soft-clipping).--end-to-end
End-to-end alignment (default).--very-fast
Preset for very fast alignment.--sensitive
Preset for sensitive alignment (default).--very-sensitive
Preset for very sensitive alignment.--un file
Write unaligned reads to file.--al file
Write aligned reads to file.-q
Input files are FASTQ (default).-f
Input files are FASTA.
CAVEATS
Index must be built before alignment using bowtie2-build. Memory usage scales with genome size. Very sensitive mode is significantly slower. Paired-end alignment requires coordinated mate files. Output needs sorting for many downstream applications.
HISTORY
Bowtie2 was developed by Ben Langmead and Steven Salzberg at Johns Hopkins University, published in 2012 in Nature Methods. It succeeded the original Bowtie aligner with improved handling of longer reads and gapped alignments. Bowtie2 has become one of the most widely used aligners in genomics research, particularly for DNA-seq and ChIP-seq analysis.


