Manual

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (whole-genome, transcriptome, and exome sequencing data) against the general human population (as well as against a single reference genome). Based on GCSA (an extension of BWT for a graph), we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents general population, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover human population). These small indexes (called local indexes) combined with several alignment strategies enable effective alignment of sequencing reads. This new indexing scheme is called Hierarchical Graph FM index (HGFM). We have developed HISAT 2 based on the HISAT and Bowtie2 implementations. HISAT2 outputs alignments in SAM format, enabling interoperation with a large number of other tools (e.g. SAMtools, GATK) that use SAM. HISAT2 is distributed under the GPLv3 license, and it runs on the command line under Linux, Mac OS X and Windows.

Download HISAT2 sources and binaries from the Releases sections on the right side. Binaries are available for Intel architectures (x86_64) running Linux, and Mac OS X.

Building HISAT2 from source requires a GNU-like environment with GCC, GNU Make and other basics. It should be possible to build HISAT2 on most vanilla Linux installations or on a Mac installation with Xcode installed. HISAT2 can also be built on Windows using Cygwin or MinGW (MinGW recommended). For a MinGW build the choice of what compiler is to be used is important since this will determine if a 32 or 64 bit code can be successfully compiled using it. If there is a need to generate both 32 and 64 bit on the same machine then a multilib MinGW has to be properly installed. MSYS, the zlib library, and depending on architecture pthreads library are also required. We are recommending a 64 bit build since it has some clear advantages in real life research problems. 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 Download section on the right side. Unzip the file, change to the unzipped directory, and build the HISAT2 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.

HISAT2 is using the multithreading software model in order to speed up execution times on SMP architectures where this is possible. On POSIX platforms (like linux, Mac OS, etc) it needs the pthread library. Although it is possible to use pthread library on non-POSIX platform like Windows, due to performance reasons HISAT2 will try to use Windows native multithreading if possible.

For the support of SRA data access in HISAT2, please download and install the NCBI-NGS toolkit. When running make, specify additional variables as follow. make USE_SRA=1 NCBI_NGS_DIR=/path/to/NCBI-NGS-directory NCBI_VDB_DIR=/path/to/NCBI-NGS-directory, where NCBI_NGS_DIR and NCBI_VDB_DIR will be used in Makefile for -I and -L compilation options. For example, $(NCBI_NGS_DIR)/include and $(NCBI_NGS_DIR)/lib64 will be used.

By adding your new HISAT2 directory to your PATH environment variable, you ensure that whenever you run hisat2, hisat2-build or hisat2-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 HISAT2 by copying the HISAT2 executable files to an existing directory in your PATH, make sure that you copy all the executables, including hisat2, hisat2-align-s, hisat2-align-l, hisat2-build, hisat2-build-s, hisat2-build-l, hisat2-inspect, hisat2-inspect-s and hisat2-inspect-l.

The reporting mode governs how many alignments HISAT2 looks for, and how to report them.

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.

By default, HISAT2 may soft-clip reads near their 5’ and 3’ ends. Users can control this behavior by setting different penalties for soft-clipping (--sp) or by disallowing soft-clipping ([--no-softclip]).

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.

HISAT2 searches for up to N distinct, primary alignments for each read, where N equals the integer specified with the -k parameter. Primary alignments mean alignments whose alignment score is equal or higher than any other alignments. It is possible that multiple distinct alignments have the same score. That is, if -k 2 is specified, HISAT2 will search for at most 2 distinct alignments. 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.

HISAT2 does not “find” alignments in any specific order, so for reads that have more than N distinct, valid alignments, HISAT2 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.

When HISAT2 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:

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

The indentation indicates how subtotals relate to totals.

The hisat2, hisat2-build and hisat2-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 hisat2 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 hisat2 wrappers and not run the binaries directly.

hisat2-build can index reference genomes of any size. For genomes less than about 4 billion nucleotides in length, hisat2-build builds a “small” index using 32-bit numbers in various parts of the index. When the genome is longer, hisat2-build builds a “large” index using 64-bit numbers. Small indexes are stored in files with the .ht2 extension, and large indexes are stored in files with the .ht2l 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.

Some HISAT2 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:

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

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.

chromosome name genomic position of the flanking base on the left side of an intron genomic position of the flanking base on the right strand (+, -, and .)

’.’ indicates an unknown strand for non-canonical splice sites.

Use samtools sort to convert the BAM file to a sorted BAM file. The following command requires samtools version 1.2 or higher.

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 convenient for variant discovery. To generate variant calls in VCF format, run:

Then to view the variants, run:

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