HISAT2 Tutorial


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Overview of HISAT2

HISAT2 is a state-of-the-art bioinformatics tool designed for the fast and sensitive alignment of next-generation sequencing reads to a population of genomes or a single reference genome. It is particularly useful for both DNA and RNA sequencing data. HISAT2 stands out due to its novel indexing scheme, the Hierarchical Graph FM index (HGFM), which allows it to efficiently handle large genomic datasets with variations among individuals, such as single nucleotide polymorphisms (SNPs).

The tool is an advancement over its predecessor, TopHat2, and incorporates several innovative features to improve alignment accuracy, especially in the presence of SNPs. HISAT2 can map reads directly against transcripts and provides SNP information as an optional field in the SAM output, which is crucial for genotyping in downstream analyses. It also offers options to enhance the performance of transcript assemblers like StringTie and Cufflinks.

HISAT2's development has been supported by grants from various institutions, and it is maintained by a team of contributors led by Daehwan Kim and Steven L. Salzberg. The source code for HISAT2 is publicly available on GitHub, ensuring that the tool remains accessible and up-to-date with the latest genomic research needs.


To install HISAT2, users can download the source code or precompiled binaries from the official HISAT2 website or its GitHub repository. The installation process is straightforward and typically involves extracting the downloaded files and optionally adding the HISAT2 directory to the system's PATH environment variable for easy access to the tool's commands.

It is important to ensure that all dependencies are met and that the system meets the necessary requirements to run HISAT2. Detailed installation instructions are provided in the HISAT2 manual, which is available on the official website.

Quick Start

For users new to HISAT2, a quick start guide is available to help them begin aligning sequencing reads with minimal setup. The guide walks users through the basic steps of indexing a reference genome and aligning reads to the index. This process involves using the hisat2-build command to create an index from a reference genome and then using the hisat2 command to perform the actual alignment.

The quick start guide is designed to be user-friendly and provides example commands that can be easily adapted to the user's specific datasets and research objectives.

Code Examples Of Popular Commands

HISAT2 offers a variety of commands to cater to different alignment needs. Here are five popular commands with code examples:

  1. Building an index for a reference genome:

    hisat2-build -f reference_genome.fa reference_index

    This command creates an index named reference_index from the FASTA file reference_genome.fa.

  2. Aligning sequencing reads to the reference index:

    hisat2 -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 and outputs the alignments to output.sam.

  3. Including SNP information in the alignment:

    hisat2 -x reference_index --snp snp_info.txt -1 reads_1.fq -2 reads_2.fq -S output.sam

    This command aligns reads with SNP information provided in snp_info.txt.

  4. Directly mapping reads against transcripts:

    hisat2 -x genome_tran -1 reads_1.fq -2 reads_2.fq -S output.sam

    This command uses the genome_tran index to map reads directly against transcripts.

  5. Preparing alignments for transcript assembly:

    hisat2 --dta -x reference_index -1 reads_1.fq -2 reads_2.fq -S output.sam

    The --dta option prepares the alignments for downstream transcript assembly with tools like StringTie.

These commands showcase the flexibility and power of HISAT2 in handling various alignment scenarios. Users can refer to the HISAT2 manual for a comprehensive list of options and detailed explanations of each command.

In conclusion, HISAT2 is a versatile and efficient tool for genomic alignment, offering advanced features for handling genetic variations and supporting a wide range of downstream analyses. Its ease of use and comprehensive documentation make it an essential resource for researchers in the field of genomics and bioinformatics.