Table of Contents

Introduction

Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s of characters to relatively long (e.g. mammalian) genomes. Bowtie 2 indexes the genome with an FM Index (based on the Burrows-Wheeler Transform or BWT) to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 gigabytes of RAM. Bowtie 2 supports gapped, local, and paired-end alignment modes. Multiple processors can be used simultaneously to achieve greater alignment speed.

Bowtie 2 outputs alignments in SAM format, enabling interoperation with a large number of other tools (e.g. SAMtools, GATK) that use SAM. Bowtie 2 is distributed under the GPLv3 license, and it runs on the command line under Windows, Mac OS X and Linux.

Bowtie 2 is often the first step in pipelines for comparative genomics, including for variation calling, ChIP-seq, RNA-seq, BS-seq. Bowtie 2 and Bowtie (also called “Bowtie 1” here) are also tightly integrated into many other tools, some of which are listed here.

If you use Bowtie 2 for your published research, please cite our work. Papers describing Bowtie 2 are:

• Langmead B, Wilks C, Antonescu V, Charles R. Scaling read aligners to hundreds of threads on general-purpose processors. Bioinformatics. 2018 Jul 18. doi: 10.1093/bioinformatics/bty648.

• Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012 Mar 4;9(4):357-9. doi: 10.1038/nmeth.1923.

How is Bowtie 2 different from Bowtie 1?

Bowtie 1 was released in 2009 and was geared toward aligning the relatively short sequencing reads (up to 25-50 nucleotides) prevalent at the time. Since then, technology has improved both sequencing throughput (more nucleotides produced per sequencer per day) and read length (more nucleotides per read).

The chief differences between Bowtie 1 and Bowtie 2 are:

1. For reads longer than about 50 bp Bowtie 2 is generally faster, more sensitive, and uses less memory than Bowtie 1. For relatively short reads (e.g. less than 50 bp) Bowtie 1 is sometimes faster and/or more sensitive.

2. Bowtie 2 supports gapped alignment with affine gap penalties. Number of gaps and gap lengths are not restricted, except by way of the configurable scoring scheme. Bowtie 1 finds just ungapped alignments.

3. Bowtie 2 supports local alignment, which doesn’t require reads to align end-to-end. Local alignments might be “trimmed” (“soft clipped”) at one or both extremes in a way that optimizes alignment score. Bowtie 2 also supports end-to-end alignment which, like Bowtie 1, requires that the read align entirely.

4. There is no upper limit on read length in Bowtie 2. Bowtie 1 had an upper limit of around 1000 bp.

5. Bowtie 2 allows alignments to overlap ambiguous characters (e.g. Ns) in the reference. Bowtie 1 does not.

6. Bowtie 2 does away with Bowtie 1’s notion of alignment “stratum”, and its distinction between “Maq-like” and “end-to-end” modes. In Bowtie 2 all alignments lie along a continuous spectrum of alignment scores where the scoring scheme, similar to Needleman-Wunsch and Smith-Waterman.

7. Bowtie 2’s paired-end alignment is more flexible. E.g. for pairs that do not align in a paired fashion, Bowtie 2 attempts to find unpaired alignments for each mate.

8. Bowtie 2 reports a spectrum of mapping qualities, in contrast for Bowtie 1 which reports either 0 or high.

9. Bowtie 2 does not align colorspace reads.

Bowtie 2 is not a “drop-in” replacement for Bowtie 1. Bowtie 2’s command-line arguments and genome index format are both different from Bowtie 1’s.

What isn’t Bowtie 2?

Bowtie 2 is geared toward aligning relatively short sequencing reads to long genomes. That said, it handles arbitrarily small reference sequences (e.g. amplicons) and very long reads (i.e. upwards of 10s or 100s of kilobases), though it is slower in those settings. It is optimized for the read lengths and error modes yielded by typical Illumina sequencers.

Bowtie 2 does not support alignment of colorspace reads. (Bowtie 1 does.)

Obtaining Bowtie 2

Bowtie 2 is available from various package managers, notably Bioconda. With Bioconda installed, you should be able to install Bowtie 2 with conda install bowtie2.

Containerized versions of Bowtie 2 are also available via the Biocontainers project (e.g. via Docker Hub).

You can also download Bowtie 2 sources and binaries from the Download section of the Sourceforge site. Binaries are available for the x86_64 architecture running Linux, Mac OS X, and Windows. If you plan to compile Bowtie 2 yourself, make sure to get the source package, i.e., the filename that ends in “-source.zip”.

Building from source

Building Bowtie 2 from source requires a GNU-like environment with GCC, GNU Make and other basics. It should be possible to build Bowtie 2 on most vanilla Linux installations or on a Mac installation with Xcode installed. (But see note about the TBB library below). Bowtie 2 can also be built on Windows using a 64-bit MinGW distribution and MSYS. In order to simplify the MinGW setup it might be worth investigating popular MinGW personal builds since these are coming already prepared with most of the toolchains needed.

First, download the source package from the sourceforge site. Make sure you’re getting the source package; the file downloaded should end in -source.zip. Unzip the file, change to the unzipped directory, and build the Bowtie 2 tools by running GNU make (usually with the command make, but sometimes with gmake) with no arguments. If building with MinGW, run make from the MSYS environment.

Bowtie 2 can be run on many threads. By default, Bowtie 2 uses the Threading Building Blocks library (TBB) for this. If TBB is not available on your system (e.g. make prints an error like tbb/mutex.h: No such file or directory), you can install it yourself from source (see Threading Building Blocks library) or install it using your operating system’s preferred package manager. The table below list some of the commands for a few of the more popular operating systems.

If all fails Bowtie 2 can be built with make NO_TBB=1 to use pthreads or Windows native multithreading instead.

The Bowtie 2 Makefile also includes recipes for basic automatic dependency management. Running make static-libs && make STATIC_BUILD=1 will issue a series of commands that will: 1. download TBB and zlib 2. compile them as static libraries 3. link the resulting libraries to the compiled Bowtie 2 binaries

As of version 2.3.5 bowtie2 now supports aligning SRA reads. Prepackaged builds will include a package that supports SRA. If you’re building bowtie2 from source please make sure that the Java runtime is available on your system. You can then proceed with the build by running make sra-deps && make USE_SRA=1.

Adding to PATH

By adding your new Bowtie 2 directory to your PATH environment variable, you ensure that whenever you run bowtie2, bowtie2-build or bowtie2-inspect from the command line, you will get the version you just installed without having to specify the entire path. This is recommended for most users. To do this, follow your operating system’s instructions for adding the directory to your PATH.

If you would like to install Bowtie 2 by copying the Bowtie 2 executable files to an existing directory in your PATH, make sure that you copy all the executables, including bowtie2, bowtie2-align-s, bowtie2-align-l, bowtie2-build, bowtie2-build-s, bowtie2-build-l, bowtie2-inspect, bowtie2-inspect-s and bowtie2-inspect-l.

The bowtie2 aligner

bowtie2 takes a Bowtie 2 index and a set of sequencing read files and outputs a set of alignments in SAM format.

“Alignment” is the process by which we discover how and where the read sequences are similar to the reference sequence. An “alignment” is a result from this process, specifically: an alignment is a way of “lining up” some or all of the characters in the read with some characters from the reference in a way that reveals how they’re similar. For example:

  Read:      GACTGGGCGATCTCGACTTCG
             |||||  |||||||||| |||
  Reference: GACTG--CGATCTCGACATCG

Where dash symbols represent gaps and vertical bars show where aligned characters match.

We use alignment to make an educated guess as to where a read originated with respect to the reference genome. It’s not always possible to determine this with certainty. For instance, if the reference genome contains several long stretches of As (AAAAAAAAA etc.) and the read sequence is a short stretch of As (AAAAAAA), we cannot know for certain exactly where in the sea of As the read originated.

End-to-end alignment versus local alignment

By default, Bowtie 2 performs end-to-end read alignment. That is, it searches for alignments involving all of the read characters. This is also called an “untrimmed” or “unclipped” alignment.

When the –local option is specified, Bowtie 2 performs local read alignment. In this mode, Bowtie 2 might “trim” or “clip” some read characters from one or both ends of the alignment if doing so maximizes the alignment score.

End-to-end alignment example

The following is an “end-to-end” alignment because it involves all the characters in the read. Such an alignment can be produced by Bowtie 2 in either end-to-end mode or in local mode.

Read:      GACTGGGCGATCTCGACTTCG
Reference: GACTGCGATCTCGACATCG

Alignment:
  Read:      GACTGGGCGATCTCGACTTCG
             |||||  |||||||||| |||
  Reference: GACTG--CGATCTCGACATCG

Local alignment example

The following is a “local” alignment because some of the characters at the ends of the read do not participate. In this case, 4 characters are omitted (or “soft trimmed” or “soft clipped”) from the beginning and 3 characters are omitted from the end. This sort of alignment can be produced by Bowtie 2 only in local mode.

Read:      ACGGTTGCGTTAATCCGCCACG
Reference: TAACTTGCGTTAAATCCGCCTGG

Alignment:
  Read:      ACGGTTGCGTTAA-TCCGCCACG
                 ||||||||| ||||||
  Reference: TAACTTGCGTTAAATCCGCCTGG

Scores: higher = more similar

An alignment score quantifies how similar the read sequence is to the reference sequence aligned to. The higher the score, the more similar they are. A score is calculated by subtracting penalties for each difference (mismatch, gap, etc.) and, in local alignment mode, adding bonuses for each match.

The scores can be configured with the --ma (match bonus), --mp (mismatch penalty), --np (penalty for having an N in either the read or the reference), --rdg (affine read gap penalty) and --rfg (affine reference gap penalty) options.

End-to-end alignment score example

A mismatched base at a high-quality position in the read receives a penalty of -6 by default. A length-2 read gap receives a penalty of -11 by default (-5 for the gap open, -3 for the first extension, -3 for the second extension). Thus, in end-to-end alignment mode, if the read is 50 bp long and it matches the reference exactly except for one mismatch at a high-quality position and one length-2 read gap, then the overall score is -(6 + 11) = -17.

The best possible alignment score in end-to-end mode is 0, which happens when there are no differences between the read and the reference.

Local alignment score example

A mismatched base at a high-quality position in the read receives a penalty of -6 by default. A length-2 read gap receives a penalty of -11 by default (-5 for the gap open, -3 for the first extension, -3 for the second extension). A base that matches receives a bonus of +2 be default. Thus, in local alignment mode, if the read is 50 bp long and it matches the reference exactly except for one mismatch at a high-quality position and one length-2 read gap, then the overall score equals the total bonus, 2 * 49, minus the total penalty, 6 + 11, = 81.

The best possible score in local mode equals the match bonus times the length of the read. This happens when there are no differences between the read and the reference.

Valid alignments meet or exceed the minimum score threshold

For an alignment to be considered “valid” (i.e. “good enough”) by Bowtie 2, it must have an alignment score no less than the minimum score threshold. The threshold is configurable and is expressed as a function of the read length. In end-to-end alignment mode, the default minimum score threshold is -0.6 + -0.6 * L, where L is the read length. In local alignment mode, the default minimum score threshold is 20 + 8.0 * ln(L), where L is the read length. This can be configured with the --score-min option. For details on how to set options like --score-min that correspond to functions, see the section on setting function options.

Mapping quality: higher = more unique

The aligner cannot always assign a read to its point of origin with high confidence. For instance, a read that originated inside a repeat element might align equally well to many occurrences of the element throughout the genome, leaving the aligner with no basis for preferring one over the others.

Aligners characterize their degree of confidence in the point of origin by reporting a mapping quality: a non-negative integer Q = -10 log10 p, where p is an estimate of the probability that the alignment does not correspond to the read’s true point of origin. Mapping quality is sometimes abbreviated MAPQ, and is recorded in the SAM MAPQ field.

Mapping quality is related to “uniqueness.” We say an alignment is unique if it has a much higher alignment score than all the other possible alignments. The bigger the gap between the best alignment’s score and the second-best alignment’s score, the more unique the best alignment, and the higher its mapping quality should be.

Accurate mapping qualities are useful for downstream tools like variant callers. For instance, a variant caller might choose to ignore evidence from alignments with mapping quality less than, say, 10. A mapping quality of 10 or less indicates that there is at least a 1 in 10 chance that the read truly originated elsewhere.

Aligning pairs

A “paired-end” or “mate-pair” read consists of pair of mates, called mate 1 and mate 2. Pairs come with a prior expectation about (a) the relative orientation of the mates, and (b) the distance separating them on the original DNA molecule. Exactly what expectations hold for a given dataset depends on the lab procedures used to generate the data. For example, a common lab procedure for producing pairs is Illumina’s Paired-end Sequencing Assay, which yields pairs with a relative orientation of FR (“forward, reverse”) meaning that if mate 1 came from the Watson strand, mate 2 very likely came from the Crick strand and vice versa. Also, this protocol yields pairs where the expected genomic distance from end to end is about 200-500 base pairs.

For simplicity, this manual uses the term “paired-end” to refer to any pair of reads with some expected relative orientation and distance. Depending on the protocol, these might actually be referred to as “paired-end” or “mate-paired.” Also, we always refer to the individual sequences making up the pair as “mates.”

Paired inputs

Pairs are often stored in a pair of files, one file containing the mate 1s and the other containing the mates 2s. The first mate in the file for mate 1 forms a pair with the first mate in the file for mate 2, the second with the second, and so on. When aligning pairs with Bowtie 2, specify the file with the mate 1s mates using the -1 argument and the file with the mate 2s using the -2 argument. This causes Bowtie 2 to take the paired nature of the reads into account when aligning them.

Paired SAM output

When Bowtie 2 prints a SAM alignment for a pair, it prints two records (i.e. two lines of output), one for each mate. The first record describes the alignment for mate 1 and the second record describes the alignment for mate 2. In both records, some of the fields of the SAM record describe various properties of the alignment; for instance, the 7th and 8th fields (RNEXT and PNEXT respectively) indicate the reference name and position where the other mate aligned, and the 9th field indicates the inferred length of the DNA fragment from which the two mates were sequenced. See the SAM specification for more details regarding these fields.

Concordant pairs match pair expectations, discordant pairs don’t

A pair that aligns with the expected relative mate orientation and with the expected range of distances between mates is said to align “concordantly”. If both mates have unique alignments, but the alignments do not match paired-end expectations (i.e. the mates aren’t in the expected relative orientation, or aren’t within the expected distance range, or both), the pair is said to align “discordantly”. Discordant alignments may be of particular interest, for instance, when seeking structural variants.

The expected relative orientation of the mates is set using the --ff, --fr, or --rf options. The expected range of inter-mates distances (as measured from the furthest extremes of the mates; also called “outer distance”) is set with the -I and -X options. Note that setting -I and -X far apart makes Bowtie 2 slower. See documentation for -I and -X.

To declare that a pair aligns discordantly, Bowtie 2 requires that both mates align uniquely. This is a conservative threshold, but this is often desirable when seeking structural variants.

By default, Bowtie 2 searches for both concordant and discordant alignments, though searching for discordant alignments can be disabled with the --no-discordant option.

Mixed mode: paired where possible, unpaired otherwise

If Bowtie 2 cannot find a paired-end alignment for a pair, by default it will go on to look for unpaired alignments for the constituent mates. This is called “mixed mode.” To disable mixed mode, set the --no-mixed option.

Bowtie 2 runs a little faster in --no-mixed mode, but will only consider alignment status of pairs per se, not individual mates.

Some SAM FLAGS describe paired-end properties

The SAM FLAGS field, the second field in a SAM record, has multiple bits that describe the paired-end nature of the read and alignment. The first (least significant) bit (1 in decimal, 0x1 in hexadecimal) is set if the read is part of a pair. The second bit (2 in decimal, 0x2 in hexadecimal) is set if the read is part of a pair that aligned in a paired-end fashion. The fourth bit (8 in decimal, 0x8 in hexadecimal) is set if the read is part of a pair and the other mate in the pair had at least one valid alignment. The sixth bit (32 in decimal, 0x20 in hexadecimal) is set if the read is part of a pair and the other mate in the pair aligned to the Crick strand (or, equivalently, if the reverse complement of the other mate aligned to the Watson strand). The seventh bit (64 in decimal, 0x40 in hexadecimal) is set if the read is mate 1 in a pair. The eighth bit (128 in decimal, 0x80 in hexadecimal) is set if the read is mate 2 in a pair. See the SAM specification for a more detailed description of the FLAGS field.

Some SAM optional fields describe more paired-end properties

The last several fields of each SAM record usually contain SAM optional fields, which are simply tab-separated strings conveying additional information about the reads and alignments. A SAM optional field is formatted like this: “XP:i:1” where “XP” is the TAG, “i” is the TYPE (“integer” in this case), and “1” is the VALUE. See the SAM specification for details regarding SAM optional fields.

Mates can overlap, contain, or dovetail each other

The fragment and read lengths might be such that alignments for the two mates from a pair overlap each other. Consider this example:

(For these examples, assume we expect mate 1 to align to the left of mate 2.)

Mate 1:    GCAGATTATATGAGTCAGCTACGATATTGTT
Mate 2:                               TGTTTGGGGTGACACATTACGCGTCTTTGAC
Reference: GCAGATTATATGAGTCAGCTACGATATTGTTTGGGGTGACACATTACGCGTCTTTGAC

It’s also possible, though unusual, for one mate alignment to contain the other, as in these examples:

Mate 1:    GCAGATTATATGAGTCAGCTACGATATTGTTTGGGGTGACACATTACGC
Mate 2:                               TGTTTGGGGTGACACATTACGC
Reference: GCAGATTATATGAGTCAGCTACGATATTGTTTGGGGTGACACATTACGCGTCTTTGAC

Mate 1:                   CAGCTACGATATTGTTTGGGGTGACACATTACGC
Mate 2:                      CTACGATATTGTTTGGGGTGAC
Reference: GCAGATTATATGAGTCAGCTACGATATTGTTTGGGGTGACACATTACGCGTCTTTGAC

And it’s also possible, though unusual, for the mates to “dovetail”, with the mates seemingly extending “past” each other as in this example:

Mate 1:                 GTCAGCTACGATATTGTTTGGGGTGACACATTACGC
Mate 2:            TATGAGTCAGCTACGATATTGTTTGGGGTGACACAT                   
Reference: GCAGATTATATGAGTCAGCTACGATATTGTTTGGGGTGACACATTACGCGTCTTTGAC

In some situations, it’s desirable for the aligner to consider all these cases as “concordant” as long as other paired-end constraints are not violated. Bowtie 2’s default behavior is to consider overlapping and containing as being consistent with concordant alignment. By default, dovetailing is considered inconsistent with concordant alignment.

These defaults can be overridden. Setting --no-overlap causes Bowtie 2 to consider overlapping mates as non-concordant. Setting --no-contain causes Bowtie 2 to consider cases where one mate alignment contains the other as non-concordant. Setting --dovetail causes Bowtie 2 to consider cases where the mate alignments dovetail as concordant.

Reporting

The reporting mode governs how many alignments Bowtie 2 looks for, and how to report them. Bowtie 2 has three distinct reporting modes. The default reporting mode is similar to the default reporting mode of many other read alignment tools, including BWA. It is also similar to Bowtie 1’s -M alignment mode.

In general, when we say that a read has an alignment, we mean that it has a valid alignment. When we say that a read has multiple alignments, we mean that it has multiple alignments that are valid and distinct from one another.

Distinct alignments map a read to different places

Two alignments for the same individual read are “distinct” if they map the same read to different places. Specifically, we say that two alignments are distinct if there are no alignment positions where a particular read offset is aligned opposite a particular reference offset in both alignments with the same orientation. E.g. if the first alignment is in the forward orientation and aligns the read character at read offset 10 to the reference character at chromosome 3, offset 3,445,245, and the second alignment is also in the forward orientation and also aligns the read character at read offset 10 to the reference character at chromosome 3, offset 3,445,245, they are not distinct alignments.

Two alignments for the same pair are distinct if either the mate 1s in the two paired-end alignments are distinct or the mate 2s in the two alignments are distinct or both.

Default mode: search for multiple alignments, report the best one

By default, Bowtie 2 searches for distinct, valid alignments for each read. When it finds a valid alignment, it generally will continue to look for alignments that are nearly as good or better. It will eventually stop looking, either because it exceeded a limit placed on search effort (see -D and -R) or because it already knows all it needs to know to report an alignment. Information from the best alignments are used to estimate mapping quality (the MAPQ SAM field) and to set SAM optional fields, such as AS:i and XS:i. Bowtie 2 does not guarantee that the alignment reported is the best possible in terms of alignment score.

See also: -D, which puts an upper limit on the number of dynamic programming problems (i.e. seed extensions) that can “fail” in a row before Bowtie 2 stops searching. Increasing -D makes Bowtie 2 slower, but increases the likelihood that it will report the correct alignment for a read that aligns many places.

See also: -R, which sets the maximum number of times Bowtie 2 will “re-seed” when attempting to align a read with repetitive seeds. Increasing -R makes Bowtie 2 slower, but increases the likelihood that it will report the correct alignment for a read that aligns many places.

-k mode: search for one or more alignments, report each

In -k mode, Bowtie 2 searches for up to N distinct, valid alignments for each read, where N equals the integer specified with the -k parameter. That is, if -k 2 is specified, Bowtie 2 will search for at most 2 distinct alignments. It reports all alignments found, in descending order by alignment score. The alignment score for a paired-end alignment equals the sum of the alignment scores of the individual mates. Each reported read or pair alignment beyond the first has the SAM ‘secondary’ bit (which equals 256) set in its FLAGS field. See the SAM specification for details.

Bowtie 2 does not “find” alignments in any specific order, so for reads that have more than N distinct, valid alignments, Bowtie 2 does not guarantee that the N alignments reported are the best possible in terms of alignment score. Still, this mode can be effective and fast in situations where the user cares more about whether a read aligns (or aligns a certain number of times) than where exactly it originated.

-a mode: search for and report all alignments

-a mode is similar to -k mode except that there is no upper limit on the number of alignments Bowtie 2 should report. Alignments are reported in descending order by alignment score. The alignment score for a paired-end alignment equals the sum of the alignment scores of the individual mates. Each reported read or pair alignment beyond the first has the SAM ‘secondary’ bit (which equals 256) set in its FLAGS field. See the SAM specification for details.

Some tools are designed with this reporting mode in mind. Bowtie 2 is not! For very large genomes, this mode is very slow.

Randomness in Bowtie 2

Bowtie 2’s search for alignments for a given read is “randomized.” That is, when Bowtie 2 encounters a set of equally-good choices, it uses a pseudo-random number to choose. For example, if Bowtie 2 discovers a set of 3 equally-good alignments and wants to decide which to report, it picks a pseudo-random integer 0, 1 or 2 and reports the corresponding alignment. Arbitrary choices can crop up at various points during alignment.

The pseudo-random number generator is re-initialized for every read, and the seed used to initialize it is a function of the read name, nucleotide string, quality string, and the value specified with --seed. If you run the same version of Bowtie 2 on two reads with identical names, nucleotide strings, and quality strings, and if --seed is set the same for both runs, Bowtie 2 will produce the same output; i.e., it will align the read to the same place, even if there are multiple equally good alignments. This is intuitive and desirable in most cases. Most users expect Bowtie to produce the same output when run twice on the same input.

However, when the user specifies the --non-deterministic option, Bowtie 2 will use the current time to re-initialize the pseudo-random number generator. When this is specified, Bowtie 2 might report different alignments for identical reads. This is counter-intuitive for some users, but might be more appropriate in situations where the input consists of many identical reads.

Multiseed heuristic

To rapidly narrow the number of possible alignments that must be considered, Bowtie 2 begins by extracting substrings (“seeds”) from the read and its reverse complement and aligning them in an ungapped fashion with the help of the FM Index. This is “multiseed alignment” and it is similar to what Bowtie 1 does, except Bowtie 1 attempts to align the entire read this way.

This initial step makes Bowtie 2 much faster than it would be without such a filter, but at the expense of missing some valid alignments. For instance, it is possible for a read to have a valid overall alignment but to have no valid seed alignments because each potential seed alignment is interrupted by too many mismatches or gaps.

The trade-off between speed and sensitivity/accuracy can be adjusted by setting the seed length (-L), the interval between extracted seeds (-i), and the number of mismatches permitted per seed (-N). For more sensitive alignment, set these parameters to (a) make the seeds closer together, (b) make the seeds shorter, and/or (c) allow more mismatches. You can adjust these options one-by-one, though Bowtie 2 comes with some useful combinations of options prepackaged as “preset options.”

-D and -R are also options that adjust the trade-off between speed and sensitivity/accuracy.

FM Index memory footprint

Bowtie 2 uses the FM Index to find ungapped alignments for seeds. This step accounts for the bulk of Bowtie 2’s memory footprint, as the FM Index itself is typically the largest data structure used. For instance, the memory footprint of the FM Index for the human genome is about 3.2 gigabytes of RAM.

Ambiguous characters

Non-whitespace characters besides A, C, G or T are considered “ambiguous.” N is a common ambiguous character that appears in reference sequences. Bowtie 2 considers all ambiguous characters in the reference (including IUPAC nucleotide codes) to be Ns.

Bowtie 2 allows alignments to overlap ambiguous characters in the reference. An alignment position that contains an ambiguous character in the read, reference, or both, is penalized according to --np. --n-ceil sets an upper limit on the number of positions that may contain ambiguous reference characters in a valid alignment. The optional field XN:i reports the number of ambiguous reference characters overlapped by an alignment.

Note that the multiseed heuristic cannot find seed alignments that overlap ambiguous reference characters. For an alignment overlapping an ambiguous reference character to be found, it must have one or more seed alignments that do not overlap ambiguous reference characters.

Presets: setting many settings at once

Bowtie 2 comes with some useful combinations of parameters packaged into shorter “preset” parameters. For example, running Bowtie 2 with the --very-sensitive option is the same as running with options: -D 20 -R 3 -N 0 -L 20 -i S,1,0.50. The preset options that come with Bowtie 2 are designed to cover a wide area of the speed/sensitivity/accuracy trade-off space, with the presets ending in fast generally being faster but less sensitive and less accurate, and the presets ending in sensitive generally being slower but more sensitive and more accurate. See the documentation for the preset options for details.

Filtering

Some reads are skipped or “filtered out” by Bowtie 2. For example, reads may be filtered out because they are extremely short or have a high proportion of ambiguous nucleotides. Bowtie 2 will still print a SAM record for such a read, but no alignment will be reported and the YF:i SAM optional field will be set to indicate the reason the read was filtered.

• YF:Z:LN: the read was filtered because it had length less than or equal to the number of seed mismatches set with the -N option.
• YF:Z:NS: the read was filtered because it contains a number of ambiguous characters (usually N or .) greater than the ceiling specified with --n-ceil.
• YF:Z:SC: the read was filtered because the read length and the match bonus (set with --ma) are such that the read can’t possibly earn an alignment score greater than or equal to the threshold set with --score-min
• YF:Z:QC: the read was filtered because it was marked as failing quality control and the user specified the --qc-filter option. This only happens when the input is in Illumina’s QSEQ format (i.e. when --qseq is specified) and the last (11th) field of the read’s QSEQ record contains 1.

If a read could be filtered for more than one reason, the value YF:Z flag will reflect only one of those reasons.

Alignment summary

When Bowtie 2 finishes running, it prints messages summarizing what happened. These messages are printed to the “standard error” (“stderr”) filehandle. For datasets consisting of unpaired reads, the summary might look like this:

20000 reads; of these:
  20000 (100.00%) were unpaired; of these:
    1247 (6.24%) aligned 0 times
    18739 (93.69%) aligned exactly 1 time
    14 (0.07%) aligned >1 times
93.77% overall alignment rate

For datasets consisting of pairs, the summary might look like this:

10000 reads; of these:
  10000 (100.00%) were paired; of these:
    650 (6.50%) aligned concordantly 0 times
    8823 (88.23%) aligned concordantly exactly 1 time
    527 (5.27%) aligned concordantly >1 times
    ----
    650 pairs aligned concordantly 0 times; of these:
      34 (5.23%) aligned discordantly 1 time
    ----
    616 pairs aligned 0 times concordantly or discordantly; of these:
      1232 mates make up the pairs; of these:
        660 (53.57%) aligned 0 times
        571 (46.35%) aligned exactly 1 time
        1 (0.08%) aligned >1 times
96.70% overall alignment rate

The indentation indicates how subtotals relate to totals.

Wrapper scripts

The bowtie2, bowtie2-build and bowtie2-inspect executables are actually wrapper scripts that call binary programs as appropriate. The wrappers shield users from having to distinguish between “small” and “large” index formats, discussed briefly in the following section. Also, the bowtie2 wrapper provides some key functionality, like the ability to handle compressed inputs, and the functionality for --un, --al and related options.

It is recommended that you always run the bowtie2 wrappers and not run the binaries directly.

Small and large indexes

bowtie2-build can index reference genomes of any size. For genomes less than about 4 billion nucleotides in length, bowtie2-build builds a “small” index using 32-bit numbers in various parts of the index. When the genome is longer, bowtie2-build builds a “large” index using 64-bit numbers. Small indexes are stored in files with the .bt2 extension, and large indexes are stored in files with the .bt2l extension. The user need not worry about whether a particular index is small or large; the wrapper scripts will automatically build and use the appropriate index.

Performance tuning

1. If your computer has multiple processors/cores, use -p

   The -p option causes Bowtie 2 to launch a specified number of parallel search threads. Each thread runs on a different processor/core and all threads find alignments in parallel, increasing alignment throughput by approximately a multiple of the number of threads (though in practice, speedup is somewhat worse than linear).

2. If reporting many alignments per read, try reducing bowtie2-build --offrate

   If you are using -k or -a options and Bowtie 2 is reporting many alignments per read, using an index with a denser SA sample can speed things up considerably. To do this, specify a smaller-than-default -o/--offrate value when running bowtie2-build. A denser SA sample yields a larger index, but is also particularly effective at speeding up alignment when many alignments are reported per read.

3. If bowtie2 “thrashes”, try increasing bowtie2-build --offrate

   If bowtie2 runs very slowly on a relatively low-memory computer, try setting -o/--offrate to a larger value when building the index. This decreases the memory footprint of the index.

Command Line

Setting function options

Some Bowtie 2 options specify a function rather than an individual number or setting. In these cases the user specifies three parameters: (a) a function type F, (b) a constant term B, and (c) a coefficient A. The available function types are constant (C), linear (L), square-root (S), and natural log (G). The parameters are specified as F,B,A - that is, the function type, the constant term, and the coefficient are separated by commas with no whitespace. The constant term and coefficient may be negative and/or floating-point numbers.

For example, if the function specification is L,-0.4,-0.6, then the function defined is:

f(x) = -0.4 + -0.6 * x

If the function specification is G,1,5.4, then the function defined is:

f(x) = 1.0 + 5.4 * ln(x)

See the documentation for the option in question to learn what the parameter x is for. For example, in the case if the --score-min option, the function f(x) sets the minimum alignment score necessary for an alignment to be considered valid, and x is the read length.

Usage

bowtie2 [options]* -x <bt2-idx> {-1 <m1> -2 <m2> | -U <r> | --interleaved <i> | --sra-acc <acc> | b <bam>} -S [<sam>]

Main arguments

-x <bt2-idx>

-1 <m1>

-2 <m2>

-U <r>

--interleaved

--sra-acc

-b <bam>

-S <sam>

Options

Input options

-q

--tab5

--tab6

--qseq

-f

-r

-F k:<int>,i:<int>

-c

-s/--skip <int>

-u/--qupto <int>

-5/--trim5 <int>

-3/--trim3 <int>

--trim-to [3:|5:]<int>

--phred33

--phred64

--solexa-quals

--int-quals

Preset options in --end-to-end mode

--very-fast

--fast

--sensitive

--very-sensitive

Preset options in --local mode

--very-fast-local

--fast-local

--sensitive-local

--very-sensitive-local

Alignment options

-N <int>

-L <int>

-i <func>

Read:      TAGCTACGCTCTACGCTATCATGCATAAAC
Seed 1 fw: TAGCTACGCT
Seed 1 rc: AGCGTAGCTA
Seed 2 fw:       CGCTCTACGC
Seed 2 rc:       GCGTAGAGCG
Seed 3 fw:             ACGCTATCAT
Seed 3 rc:             ATGATAGCGT
Seed 4 fw:                   TCATGCATAA
Seed 4 rc:                   TTATGCATGA

--n-ceil <func>

--dpad <int>

--gbar <int>

--ignore-quals

--nofw/--norc

--no-1mm-upfront

--end-to-end

--local

Scoring options

--ma <int>

--mp MX,MN

--np <int>

--rdg <int1>,<int2>

--rfg <int1>,<int2>

--score-min <func>

Reporting options

-k <int>

-a

Effort options

-D <int>

-R <int>

Paired-end options

-I/--minins <int>

-X/--maxins <int>

--fr/--rf/--ff

--no-mixed

--no-discordant

--dovetail

--no-contain

--no-overlap

BAM options

--align-paired-reads

--preserve-tags

Output options

-t/--time

--un <path>
--un-gz <path>
--un-bz2 <path>
--un-lz4 <path>

--al <path>
--al-gz <path>
--al-bz2 <path>
--al-lz4 <path>

--un-conc <path>
--un-conc-gz <path>
--un-conc-bz2 <path>
--un-conc-lz4 <path>

--al-conc <path>
--al-conc-gz <path>
--al-conc-bz2 <path>
--al-conc-lz4 <path>

--quiet

--met-file <path>

--met-stderr <path>

--met <int>

SAM options

--no-unal

--no-hd

--no-sq

--rg-id <text>

--rg <text>

--omit-sec-seq

--soft-clipped-unmapped-tlen

--sam-no-qname-trunc

--xeq

Performance options

-o/--offrate <int>

-p/--threads NTHREADS

--reorder

--mm

Other options

--qc-filter

--seed <int>

--non-deterministic

--version

-h/--help

SAM output

Following is a brief description of the SAM format as output by bowtie2. For more details, see the SAM format specification.

By default, bowtie2 prints a SAM header with @HD, @SQ and @PG lines. When one or more --rg arguments are specified, bowtie2 will also print an @RG line that includes all user-specified --rg tokens separated by tabs.

Each subsequent line describes an alignment or, if the read failed to align, a read. Each line is a collection of at least 12 fields separated by tabs; from left to right, the fields are:

1. Name of read that aligned.

   Note that the SAM specification disallows whitespace in the read name. If the read name contains any whitespace characters, Bowtie 2 will truncate the name at the first whitespace character. This is similar to the behavior of other tools. The standard behavior of truncating at the first whitespace can be suppressed with --sam-no-qname-trunc at the expense of generating non-standard SAM.

2. Sum of all applicable flags. Flags relevant to Bowtie are:

   1	The read is one of a pair
   2	The alignment is one end of a proper paired-end alignment
   4	The read has no reported alignments
   8	The read is one of a pair and has no reported alignments
   16	The alignment is to the reverse reference strand
   32	The other mate in the paired-end alignment is aligned to the reverse reference strand
   64	The read is mate 1 in a pair
   128	The read is mate 2 in a pair

   Thus, an unpaired read that aligns to the reverse reference strand will have flag 16. A paired-end read that aligns and is the first mate in the pair will have flag 83 (= 64 + 16 + 2 + 1).

3. Name of reference sequence where alignment occurs

4. 1-based offset into the forward reference strand where leftmost character of the alignment occurs

5. Mapping quality

6. CIGAR string representation of alignment

7. Name of reference sequence where mate’s alignment occurs. Set to = if the mate’s reference sequence is the same as this alignment’s, or * if there is no mate.

8. 1-based offset into the forward reference strand where leftmost character of the mate’s alignment occurs. Offset is 0 if there is no mate.

9. Inferred fragment length. Size is negative if the mate’s alignment occurs upstream of this alignment. Size is 0 if the mates did not align concordantly. However, size is non-0 if the mates aligned discordantly to the same chromosome.

10. Read sequence (reverse-complemented if aligned to the reverse strand)

11. ASCII-encoded read qualities (reverse-complemented if the read aligned to the reverse strand). The encoded quality values are on the Phred quality scale and the encoding is ASCII-offset by 33 (ASCII char !), similarly to a FASTQ file.

12. Optional fields. Fields are tab-separated. bowtie2 outputs zero or more of these optional fields for each alignment, depending on the type of the alignment:

AS:i:<N>

XS:i:<N>

YS:i:<N>

XN:i:<N>

XM:i:<N>

XO:i:<N>

XG:i:<N>

NM:i:<N>

YF:Z:<S>

YT:Z:<S>

MD:Z:<S>

The bowtie2-build indexer

bowtie2-build builds a Bowtie index from a set of DNA sequences. bowtie2-build outputs a set of 6 files with suffixes .1.bt2, .2.bt2, .3.bt2, .4.bt2, .rev.1.bt2, and .rev.2.bt2. In the case of a large index these suffixes will have a bt2l termination. These files together constitute the index: they are all that is needed to align reads to that reference. The original sequence FASTA files are no longer used by Bowtie 2 once the index is built.

Bowtie 2’s .bt2 index format is different from Bowtie 1’s .ebwt format, and they are not compatible with each other.

Use of Karkkainen’s blockwise algorithm allows bowtie2-build to trade off between running time and memory usage. bowtie2-build has three options governing how it makes this trade: -p/--packed, --bmax/--bmaxdivn, and --dcv. By default, bowtie2-build will automatically search for the settings that yield the best running time without exhausting memory. This behavior can be disabled using the -a/--noauto option.

The indexer provides options pertaining to the “shape” of the index, e.g. --offrate governs the fraction of Burrows-Wheeler rows that are “marked” (i.e., the density of the suffix-array sample; see the original FM Index paper for details). All of these options are potentially profitable trade-offs depending on the application. They have been set to defaults that are reasonable for most cases according to our experiments. See Performance tuning for details.

bowtie2-build can generate either small or large indexes. The wrapper will decide which based on the length of the input genome. If the reference does not exceed 4 billion characters but a large index is preferred, the user can specify --large-index to force bowtie2-build to build a large index instead.

The Bowtie 2 index is based on the FM Index of Ferragina and Manzini, which in turn is based on the Burrows-Wheeler transform. The algorithm used to build the index is based on the blockwise algorithm of Karkkainen.

Command Line

Usage:

bowtie2-build [options]* <reference_in> <bt2_base>

Main arguments

<reference_in>

<bt2_base>

Options

-f

-c

--large-index

-a/--noauto

-p/--packed

--bmax <int>

--bmaxdivn <int>

--dcv <int>

--nodc

-r/--noref

-3/--justref

-o/--offrate <int>

-t/--ftabchars <int>

--seed <int>

--cutoff <int>

-q/--quiet

--threads <int>

-h/--help

--version

The bowtie2-inspect index inspector

bowtie2-inspect extracts information from a Bowtie index about what kind of index it is and what reference sequences were used to build it. When run without any options, the tool will output a FASTA file containing the sequences of the original references (with all non-A/C/G/T characters converted to Ns). It can also be used to extract just the reference sequence names using the -n/--names option or a more verbose summary using the -s/--summary option.

Command Line

Usage:

bowtie2-inspect [options]* <bt2_base>

Main arguments

<bt2_base>

Options

-a/--across <int>

-n/--names

-s/--summary

Colorspace  <0 or 1>
SA-Sample   1 in <sample>
FTab-Chars  <chars>
Sequence-1  <name>  <len>
Sequence-2  <name>  <len>
...
Sequence-N  <name>  <len>

-v/--verbose

--version

-h/--help

Getting started with Bowtie 2: Lambda phage example

Bowtie 2 comes with some example files to get you started. The example files are not scientifically significant; we use the Lambda phage reference genome simply because it’s short, and the reads were generated by a computer program, not a sequencer. However, these files will let you start running Bowtie 2 and downstream tools right away.

First follow the manual instructions to obtain Bowtie 2. Set the BT2_HOME environment variable to point to the new Bowtie 2 directory containing the bowtie2, bowtie2-build and bowtie2-inspect binaries. This is important, as the BT2_HOME variable is used in the commands below to refer to that directory.

Indexing a reference genome

To create an index for the Lambda phage reference genome included with Bowtie 2, create a new temporary directory (it doesn’t matter where), change into that directory, and run:

$BT2_HOME/bowtie2-build $BT2_HOME/example/reference/lambda_virus.fa lambda_virus

The command should print many lines of output then quit. When the command completes, the current directory will contain four new files that all start with lambda_virus and end with .1.bt2, .2.bt2, .3.bt2, .4.bt2, .rev.1.bt2, and .rev.2.bt2. These files constitute the index - you’re done!

You can use bowtie2-build to create an index for a set of FASTA files obtained from any source, including sites such as UCSC, NCBI, and Ensembl. When indexing multiple FASTA files, specify all the files using commas to separate file names. For more details on how to create an index with bowtie2-build, see the manual section on index building. You may also want to bypass this process by obtaining a pre-built index. See using a pre-built index below for an example.

Aligning example reads

Stay in the directory created in the previous step, which now contains the lambda_virus index files. Next, run:

$BT2_HOME/bowtie2 -x lambda_virus -U $BT2_HOME/example/reads/reads_1.fq -S eg1.sam

This runs the Bowtie 2 aligner, which aligns a set of unpaired reads to the Lambda phage reference genome using the index generated in the previous step. The alignment results in SAM format are written to the file eg1.sam, and a short alignment summary is written to the console. (Actually, the summary is written to the “standard error” or “stderr” filehandle, which is typically printed to the console.)

To see the first few lines of the SAM output, run:

head eg1.sam

You will see something like this:

@HD VN:1.0  SO:unsorted
@SQ SN:gi|9626243|ref|NC_001416.1|  LN:48502
@PG ID:bowtie2  PN:bowtie2  VN:2.0.1
r1  0   gi|9626243|ref|NC_001416.1| 18401   42  122M    *   0   0   TGAATGCGAACTCCGGGACGCTCAGTAATGTGACGATAGCTGAAAACTGTACGATAAACNGTACGCTGAGGGCAGAAAAAATCGTCGGGGACATTNTAAAGGCGGCGAGCGCGGCTTTTCCG  +"@6<:27(F&5)9"B):%B+A-%5A?2$HCB0B+0=D<7E/<.03#!.F77@6B==?C"7>;))%;,3-$.A06+<-1/@@?,26">=?*@'0;$:;??G+:#+(A?9+10!8!?()?7C>  AS:i:-5 XN:i:0  XM:i:3  XO:i:0  XG:i:0  NM:i:3  MD:Z:59G13G21G26    YT:Z:UU
r2  0   gi|9626243|ref|NC_001416.1| 8886    42  275M    *   0   0   NTTNTGATGCGGGCTTGTGGAGTTCAGCCGATCTGACTTATGTCATTACCTATGAAATGTGAGGACGCTATGCCTGTACCAAATCCTACAATGCCGGTGAAAGGTGCCGGGATCACCCTGTGGGTTTATAAGGGGATCGGTGACCCCTACGCGAATCCGCTTTCAGACGTTGACTGGTCGCGTCTGGCAAAAGTTAAAGACCTGACGCCCGGCGAACTGACCGCTGAGNCCTATGACGACAGCTATCTCGATGATGAAGATGCAGACTGGACTGC (#!!'+!$""%+(+)'%)%!+!(&++)''"#"#&#"!'!("%'""("+&%$%*%%#$%#%#!)*'(#")(($&$'&%+&#%*)*#*%*')(%+!%%*"$%"#+)$&&+)&)*+!"*)!*!("&&"*#+"&"'(%)*("'!$*!!%$&&&$!!&&"(*"$&"#&!$%'%"#)$#+%*+)!&*)+(""#!)!%*#"*)*')&")($+*%%)!*)!('(%""+%"$##"#+(('!*(($*'!"*('"+)&%#&$+('**$$&+*&!#%)')'(+(!%+ AS:i:-14    XN:i:0  XM:i:8  XO:i:0  XG:i:0  NM:i:8  MD:Z:0A0C0G0A108C23G9T81T46 YT:Z:UU
r3  16  gi|9626243|ref|NC_001416.1| 11599   42  338M    *   0   0   GGGCGCGTTACTGGGATGATCGTGAAAAGGCCCGTCTTGCGCTTGAAGCCGCCCGAAAGAAGGCTGAGCAGCAGACTCAAGAGGAGAAAAATGCGCAGCAGCGGAGCGATACCGAAGCGTCACGGCTGAAATATACCGAAGAGGCGCAGAAGGCTNACGAACGGCTGCAGACGCCGCTGCAGAAATATACCGCCCGTCAGGAAGAACTGANCAAGGCACNGAAAGACGGGAAAATCCTGCAGGCGGATTACAACACGCTGATGGCGGCGGCGAAAAAGGATTATGAAGCGACGCTGTAAAAGCCGAAACAGTCCAGCGTGAAGGTGTCTGCGGGCGAT  7F$%6=$:9B@/F'>=?!D?@0(:A*)7/>9C>6#1<6:C(.CC;#.;>;2'$4D:?&B!>689?(0(G7+0=@37F)GG=>?958.D2E04C<E,*AD%G0.%$+A:'H;?8<72:88?E6((CF)6DF#.)=>B>D-="C'B080E'5BH"77':"@70#4%A5=6.2/1>;9"&-H6)=$/0;5E:<8G!@::1?2DC7C*;@*#.1C0.D>H/20,!"C-#,6@%<+<D(AG-).?&#0.00'@)/F8?B!&"170,)>:?<A7#1(A@0E#&A.*DC.E")AH"+.,5,2>5"2?:G,F"D0B8D-6$65D<D!A/38860.*4;4B<*31?6  AS:i:-22    XN:i:0  XM:i:8  XO:i:0  XG:i:0  NM:i:8  MD:Z:80C4C16A52T23G30A8T76A41   YT:Z:UU
r4  0   gi|9626243|ref|NC_001416.1| 40075   42  184M    *   0   0   GGGCCAATGCGCTTACTGATGCGGAATTACGCCGTAAGGCCGCAGATGAGCTTGTCCATATGACTGCGAGAATTAACNGTGGTGAGGCGATCCCTGAACCAGTAAAACAACTTCCTGTCATGGGCGGTAGACCTCTAAATCGTGCACAGGCTCTGGCGAAGATCGCAGAAATCAAAGCTAAGT(=8B)GD04*G%&4F,1'A>.C&7=F$,+#6!))43C,5/5+)?-/0>/D3=-,2/+.1?@->;)00!'3!7BH$G)HG+ADC'#-9F)7<7"$?&.>0)@5;4,!0-#C!15CF8&HB+B==H>7,/)C5)5*+(F5A%D,EA<(>G9E0>7&/E?4%;#'92)<5+@7:A.(BG@BG86@.G AS:i:-1 XN:i:0  XM:i:1  XO:i:0  XG:i:0  NM:i:1  MD:Z:77C106 YT:Z:UU
r5  0   gi|9626243|ref|NC_001416.1| 48010   42  138M    *   0   0   GTCAGGAAAGTGGTAAAACTGCAACTCAATTACTGCAATGCCCTCGTAATTAAGTGAATTTACAATATCGTCCTGTTCGGAGGGAAGAACGCGGGATGTTCATTCTTCATCACTTTTAATTGATGTATATGCTCTCTT  9''%<D)A03E1-*7=),:F/0!6,D9:H,<9D%:0B(%'E,(8EFG$E89B$27G8F*2+4,-!,0D5()&=(FGG:5;3*@/.0F-G#5#3->('FDFEG?)5.!)"AGADB3?6(@H(:B<>6!>;>6>G,."?%  AS:i:0  XN:i:0  XM:i:0  XO:i:0  XG:i:0  NM:i:0  MD:Z:138    YT:Z:UU
r6  16  gi|9626243|ref|NC_001416.1| 41607   42  72M2D119M   *   0   0   TCGATTTGCAAATACCGGAACATCTCGGTAACTGCATATTCTGCATTAAAAAATCAACGCAAAAAATCGGACGCCTGCAAAGATGAGGAGGGATTGCAGCGTGTTTTTAATGAGGTCATCACGGGATNCCATGTGCGTGACGGNCATCGGGAAACGCCAAAGGAGATTATGTACCGAGGAAGAATGTCGCT 1H#G;H"$E*E#&"*)2%66?=9/9'=;4)4/>@%+5#@#$4A*!<D=="8#1*A9BA=:(1+#C&.#(3#H=9E)AC*5,AC#E'536*2?)H14?>9'B=7(3H/B:+A:8%1-+#(E%&$$&14"76D?>7(&20H5%*&CF8!G5B+A4F$7(:"'?0$?G+$)B-?2<0<F=D!38BH,%=8&5@+ AS:i:-13    XN:i:0  XM:i:2  XO:i:1  XG:i:2  NM:i:4  MD:Z:72^TT55C15A47  YT:Z:UU
r7  16  gi|9626243|ref|NC_001416.1| 4692    42  143M    *   0   0   TCAGCCGGACGCGGGCGCTGCAGCCGTACTCGGGGATGACCGGTTACAACGGCATTATCGCCCGTCTGCAACAGGCTGCCAGCGATCCGATGGTGGACAGCATTCTGCTCGATATGGACANGCCCGGCGGGATGGTGGCGGGG -"/@*7A0)>2,AAH@&"%B)*5*23B/,)90.B@%=FE,E063C9?,:26$-0:,.,1849'4.;F>FA;76+5&$<C":$!A*,<B,<)@<'85D%C*:)30@85;?.B$05=@95DCDH<53!8G:F:B7/A.E':434> AS:i:-6 XN:i:0  XM:i:2  XO:i:0  XG:i:0  NM:i:2  MD:Z:98G21C22   YT:Z:UU

The first few lines (beginning with @) are SAM header lines, and the rest of the lines are SAM alignments, one line per read or mate. See the Bowtie 2 manual section on SAM output and the SAM specification for details about how to interpret the SAM file format.

Paired-end example

To align paired-end reads included with Bowtie 2, stay in the same directory and run:

$BT2_HOME/bowtie2 -x lambda_virus -1 $BT2_HOME/example/reads/reads_1.fq -2 $BT2_HOME/example/reads/reads_2.fq -S eg2.sam

This aligns a set of paired-end reads to the reference genome, with results written to the file eg2.sam.

Local alignment example

To use local alignment to align some longer reads included with Bowtie 2, stay in the same directory and run:

$BT2_HOME/bowtie2 --local -x lambda_virus -U $BT2_HOME/example/reads/longreads.fq -S eg3.sam

This aligns the long reads to the reference genome using local alignment, with results written to the file eg3.sam.

Using SAMtools/BCFtools downstream

SAMtools is a collection of tools for manipulating and analyzing SAM and BAM alignment files. BCFtools is a collection of tools for calling variants and manipulating VCF and BCF files, and it is typically distributed with SAMtools. Using these tools together allows you to get from alignments in SAM format to variant calls in VCF format. This example assumes that samtools and bcftools are installed and that the directories containing these binaries are in your PATH environment variable.

Run the paired-end example:

$BT2_HOME/bowtie2 -x $BT2_HOME/example/index/lambda_virus -1 $BT2_HOME/example/reads/reads_1.fq -2 $BT2_HOME/example/reads/reads_2.fq -S eg2.sam

Use samtools view to convert the SAM file into a BAM file. BAM is the binary format corresponding to the SAM text format. Run:

samtools view -bS eg2.sam > eg2.bam

Use samtools sort to convert the BAM file to a sorted BAM file.

samtools sort eg2.bam -o eg2.sorted.bam

We now have a sorted BAM file called eg2.sorted.bam. Sorted BAM is a useful format because the alignments are (a) compressed, which is convenient for long-term storage, and (b) sorted, which is conveneint for variant discovery. To generate variant calls in VCF format, run:

samtools mpileup -uf $BT2_HOME/example/reference/lambda_virus.fa eg2.sorted.bam | bcftools view -Ov - > eg2.raw.bcf

Then to view the variants, run:

bcftools view eg2.raw.bcf

See the official SAMtools guide to Calling SNPs/INDELs with SAMtools/BCFtools for more details and variations on this process.