Hifiasm is a fast haplotype-resolved de novo assembler for PacBio HiFi reads. It can assemble a human genome in several hours and assemble a ~30Gb California redwood genome in a few days. Hifiasm emits partially phased assemblies of quality competitive with the best assemblers. Given parental short reads or Hi-C data, it produces arguably the best haplotype-resolved assemblies so far.



Haoyu Cheng, Gregory T. Concepcion, Xiaowen Feng, Haowen Zhang & Heng Li. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nature Methods. (2021).


The easiest way to get started is to download a release. Please report any issues on github issues page.

In addition, the latest unreleased version can be found from github:

git clone https://github.com/chhylp123/hifiasm
cd hifiasm && make

Another way is to install hifiasm via bioconda:

conda install -c bioconda hifiasm

Assembly Concepts

There are different types of assemblies which are commonly used in practice (see details). Hifiasm produces primary/alternate assemblies or partially phased assemblies only with HiFi reads. Given Hi-C data or trio-binning data, hifiasm produces contiguous fully-phased assemblies, i.e. haplotype-resolved assemblies.

Why Hifiasm?

  • Hifiasm delivers high-quality assemblies. It tends to generate longer contigs and resolve more segmental duplications than other assemblers.

  • Given Hi-C reads or short reads from the parents, hifiasm can produce overall the best haplotype-resolved assembly so far. It is the assembler of choice by the Human Pangenome Project for the first batch of samples.

  • Hifiasm can purge duplications between haplotigs without relying on third-party tools such as purge_dups. Hifiasm does not need polishing tools like pilon or racon, either. This simplifies the assembly pipeline and saves running time.

  • Hifiasm is fast. It can assemble a human genome in half a day and assemble a ~30Gb redwood genome in three days. No genome is too large for hifiasm.

  • Hifiasm is trivial to install and easy to use. It does not required Python, R or C++11 compilers, and can be compiled into a single executable. The default setting works well with a variety of genomes.