Bowtie2 Tutorial


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Overview of Bowtie2

Bowtie2 is a widely-used bioinformatics tool designed for aligning sequencing reads to long reference sequences. It's particularly effective for reads ranging from about 50 to hundreds of characters, making it suitable for aligning to large genomes, such as those of mammals. One of the key features of Bowtie2 is its efficient use of memory, thanks to its use of an FM Index based on the Burrows-Wheeler Transform (BWT). This allows Bowtie2 to maintain a relatively small memory footprint, around 3.2 gigabytes for the human genome.

Bowtie2 is capable of performing gapped, local, and paired-end alignment modes, and it can utilize multiple processors to speed up the alignment process. The alignments produced by Bowtie2 are in SAM format, which is compatible with a variety of other bioinformatics tools like SAMtools and GATK.

Bowtie2 is an essential component in many comparative genomics pipelines, including those for variation calling, ChIP-seq, RNA-seq, and BS-seq. It's also integrated into numerous other tools within the bioinformatics ecosystem.

The tool is distributed under the GPLv3 license and is available for Windows, Mac OS X, Linux, and BSD operating systems. It operates via the command line, making it a tool primarily for users comfortable with terminal-based applications.

When using Bowtie2 in published research, it's important to cite the relevant papers that describe the tool, such as the work by Langmead B, Wilks C, Antonescu V, and Charles R, published in Bioinformatics in 2018, and the original paper by Langmead B and Salzberg S in Nature Methods in 2012.


To install Bowtie2, you can download the pre-compiled executables for your operating system from the Bowtie2 website or build it from source if you prefer. If you choose to download the executables, make sure to include all the necessary files in your PATH, such as bowtie2, bowtie2-align-s, bowtie2-align-l, bowtie2-build, bowtie2-build-s, bowtie2-build-l, bowtie2-inspect, bowtie2-inspect-s, and bowtie2-inspect-l. This ensures that all components of Bowtie2 are accessible from the command line.

Quick Start

Once Bowtie2 is installed, you can quickly start aligning your sequencing reads to a reference genome. The first step is to build an index of your reference genome using the bowtie2-build command. After the index is created, you can align your reads using the bowtie2 command, specifying the index and your read files as inputs. The output will be a SAM file containing the alignments.

Code Examples Of Popular Commands

Here are five popular commands that you might use with Bowtie2:

  1. Building an index for the reference genome:

    bowtie2-build reference.fa reference_index

    This command creates an index for the reference genome stored in reference.fa and names the index reference_index.

  2. Aligning single-end reads:

    bowtie2 -x reference_index -U reads.fq -S output.sam

    This aligns single-end reads from reads.fq to the reference_index and saves the alignments to output.sam.

  3. Aligning paired-end reads:

    bowtie2 -x reference_index -1 reads_1.fq -2 reads_2.fq -S output.sam

    This command aligns paired-end reads from reads_1.fq and reads_2.fq to the reference_index.

  4. Local alignment:

    bowtie2 --local -x reference_index -U reads.fq -S output.sam

    The --local option allows for local alignment, which can be more appropriate for reads that may have originated from regions with variations or insertions/deletions.

  5. Reporting multiple alignments for the same read:

    bowtie2 -x reference_index -U reads.fq -S output.sam -k 5

    The -k 5 option instructs Bowtie2 to report up to 5 valid alignments for the same read, which can be useful for analyzing reads that may map to multiple locations.

These commands represent just a few of the many options available in Bowtie2. The tool's versatility and speed make it a staple in the field of genomics and bioinformatics. Whether you're working on variant calling or analyzing gene expression, Bowtie2 provides the necessary functionality to align your sequencing data accurately and efficiently.