This is a software package pipeline for an analysis of HIV-1 genome. It can performs de novo or reference-based quasispecies assembly and identification on long-read data from either the Oxford Nanopore Sequencing Technology or the PacBio Real-Time (SMRT) Sequencing technology. This package aims to consolidate analytical tools needed for such analysis into a single, easy to use, portable Docker container, capable of functioning across different computational environments with minimal setup.

Within this pipeline, we've configured the installation of these following long-read assembers, (1) de novo long-read assemblers, which include Canu, Goldrush, Flye, and Strainline, and (2) reference-based long-read assemblers, which comprise HaploDMF, iGDA, and RVHaplo.

The Docker file comes with Strainline and MetaFlye installed. Other assemblers mentioned in the article are installed as needed to minimize the container size. (the container may take up to 15Gb for the full installation).

Based on our benchmarking study, the following optimal computational requirements are suggested:

• All assemblers should be executed in a Linux-based operating system.
• A quad-core (4 cores) or higher CPU with x86 microarchitecture is recommended,
• An 8 GB memory is sufficient but at least 16Gb is recommended.
  • Note: Strainline requires at least 16Gb baseline to run on a single threaded mode (-t 1) and scaled up roughly 4Gb per core.

This pipeline can be download directly from Docker registry Docker daemon is required for building the environment, it can be downloaded from Docker website.

# On host environment
docker pull minamini/hiv64148:latest
# Print help message
docker run --rm minamini/hiv64148:latest hiv64148 -h

For using with Singulararity user have to build the Docker image and convert it to a Singularity image singularity build hiv64148.sif docker-daemon://local/minamini/hiv64148:latest

After the setup is finished, you can attach a local directory to the container and run the pipeline with command python3 /hiv64148/scripts/main.py run, with argument -i or --input as raw reads input in FASTA or FASTQ format; -o or --output_dir as a path to output directory.

docker run \
    -v ${YOUR_WORK_DIR}:/workspace \
    --rm minamini/hiv64148:latest \
    hiv64148 run \
        -i /workspace/${YOUR_FASTQ} \
        -o /workspace/${YOUR_OUTPUT}

An example FASTQ file is provided in the example folder. Please replace ${EXAMPLE_DIR} with the location of HIV-64148/example directory.

docker run \
    -v ${EXAMPLE_DIR}:/workspace \
    --rm minamini/hiv64148:latest \
    hiv64148 run \
        -i /workspace/Simulated_x2_Major_subtype_example_1.fastq \
        -o /workspace/example_output \
        -a strainline -ag /workspace/example_settings/strainline_params.yaml

To swith between differnet assemblers, user have to specify an -a or --assember argument with the desired assembler of choice {canu,strainline,goldrush,metaflye,rvhaplo,haplodmf,igda} [default: strainline].

docker run \
    -v ./example:/workspace \
    minamini/hiv64148:latest \
    hiv64148 run \
        -i /workspace/${YOUR_FASTQ} \
        -o /workspace/${YOUR_OUTPUT} \
        --assember canu

The created environment for non built-in assembler is not persistance, if you need to reuse the assembler installed in the container pleae use docke exec to execute command on the container.

Customized parameters for each assembler can be configured using yaml file, please refer to the documentation of your selected assembler.

Examples of yaml configuration files can be found within an example folder.

docker run \
    -v ${YOUR_WORK_DIR}:/workspace \
    minamini/hiv64148:latest \
    hiv64148 run \
        -i /workspace/${YOUR_FASTQ} \
        -o /workspace/${YOUR_OUTPUT} \
        --assember strainline \
        --assember-args /workspace/example_settings/strainline_params.yaml

This pipeline can be use to assemble genome of other viral genomes as well, for de novo assemblers, Canu, MetaFlye and GoldRush, the expected genome size must be changed to the size of your desired organism (default: 9.8k for HIV-1 genome) by providing an -g/--genome-size argument.

For reference based assember the reference can be changed with -r or --reference parameter, no rebuild required.

An implementation of HIV-64148 pipeline for HIV-1 genomic surveillance. The pipeline comprises three main stages: a read quality control analysis of long-read FASTQ files, followed by assembly using either de novo or reference-based assemblers, and concluding with the identification of HIV-1 subtype and drug resistance analysis.

To identify a subtype of each haplotype, the sequences are compared against a collection of selected 32 HIV strains consists of basic clades, CRFs and laboratory clones using BLAST, subtype of each haplotype is determined by a subtype of a sequence in the collection which returns a highest bitscore when aligned to the haplotype sequence.

Finally, to perform sequence analysis the haplotype sequences are submitted to Sierra Web Service 2, a GraphQL-based web service for accessing Stanford HIV database which returns mutation and drug resistant profiles.

A selection of 12,000 HIV-1 genomes from the Los Alamos HIV-1 sequence database was included within the container to be used as a custom database for a local NCBI BLASTN used for HIV-1 subtype identification of the assembled quasispecies.

Your output will be present in the directory specified with -o argument. The output will be structured in directories as follow.

${output_directory}/
├─ NanoPlot_QC/
│  ├─ NanoPlot-report.html
│  └─ NanoStats.txt
├─ haplotype.blast.csv
├─ haplotypes.final.fasta
└─ hiv-64148_report.html  # Will not be produced in non-HIV mode

This work was supported by the following funding bodies:

• The Health Systems Research Institute (Grant No. 64-148)
• The Faculty of Medicine Research Fund, Chiang Mai University (Grant No. 099-2563)
• Support the Children Foundation, Chiang Mai, Thailand.

Wattanasombat S and Tongjai S. Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline. F1000Research 2024, 13:556 (https://doi.org/10.12688/f1000research.149577.1)