VivaxGEN MicroHaplotypes

This repository contains 2 pipelines for handling microhaplotype amplicon sequencing data:

• DADA2-based MicroHaplotype Analysis Pipeline; Original software can be found at (https://benjjneb.github.io/dada2/) but is modified for this pipeline. DADA2-based pipeline COMING SOON.

• SNP-based variant calling which output ordinary VCF file, based on vivaxGEN NGS-Pipeline.

Installation on local devices and HPCs

Note for Conda-based users! Be sure you are not in a conda environment or in the (base) conda environment prior to installing. To deactivate your conda environment or (base) environment, enter:

conda deactivate

For vivaxGEN MicroHaps sequencing pipeline, install with the following command:

"${SHELL}" <(curl -L https://raw.githubusercontent.com/vivaxgen/MicroHaps/main/install.sh)

Copy and paste command into the command line in the folder you want the install to be saved to (we recommend you create a specific tools or software folder). When prompted for "Pipeline base directory? [./vvg-MicroHaps]" press enter again for the install to proceed.

The installation requires ~ 20-45 minutes as most of R packages need to be recompiled during installation.

Once the installation finished, it will show the command to activate the pipeline, as such:

/path/to/vvg-MicroHaps/bin/activate

This activation command has to be executed before all commands of the pipeline can be run. When activated, the terminal will show the (µhaps) prompt.

The installation process also performs indexing of the reference files. However, in case that the indexing fails, please perform manual indexeing using the command:

ngs-pl initialize --target wgs

To test your install, and read about programme specifications / options:

ngs-pl run-discovery-variant-caller --help

Updating the pipeline

To update the pipeline line, assuming that the environment has been activated, run the following command:

$VVGBIN/update-pipeline.sh

Tutorial: How does the Menzies MicroHap pipeline work and what is it doing?

Introduction to SNP-based variant calling

This pipeline contains a wrapper for vivaxGEN NGS-Pipeline, a SNP-based variant calling pipeline, which has been setup to process P vivax sequence data. This pipeline will produce ordinary VCF file that can be used for further downstream analysis.

Currently, this pipeline was setup to use multi-step mode of vivaxGEN NGS-Pipeline in a single command line with GATK-based workflow to generate VCF file There is also Freebayes-based workflow, but it requires modification of the setting, which will not be covered in this documentation.

Quick Tutorial

The following instructions show how to run this pipeline. It is assumed that the pipeline has been installed.

1. Activate the environment. The terminal will show (µhaps) prompt.

	/path/to/vvg-MicroHaps/bin/activate

2. Go to the directory that will be used to process and analysis::

	cd MY_ANALYSIS_DIRECTORY

3. Provide the FASTQ reads from the sequencing result, by either copying the FASTQ files or alternatively generate soft link as necessary. The soft link approach is preferred since it will prevent duplication of the files, if the files are already reside in the local storage. The FASTQ files should be in fastq.gz format (gzip-compressed), and the filenames should reflect the sample name, eg: my-sample-01_R1.fastq.gz. If the FASTQ filenames contains something that are not part of the sample names, there is an option --underscore in the next step that can be used::

   mkdir reads
   cp /path/to/fastq/files/*.fastq.gz .
   

   or::

   ln -s SOME_SOURCE_DIR reads
   

Run command:

	ngs-pl run-discovery-variant-caller -o MY_OUTPUT reads/*.fastq.gz

example for paired-end (Illumina) reads::

	ngs-pl run-discovery-variant-caller -j 1 -o output_dir -u 4 --paired  reads/*.fastq.gz

LAPTOP USERS - It is essential that you specify "-j 1" as this limits the number of jobs running at one time. Without this argument, the pipeline will utilise too much system memory and crash. We are working on improving this issue.

The "-u 4" prompt changes depending on how your files are named as it counts the number of underscores "_" in a file name. For a sample called "sample4_date_batch_info_R1.fastq.gz", the "-u 4" argument will use result in "sample4" as the ID. For a sample called "sample_4_date_batch_pool_country_R1.fastq.gz", the argument "-u 5" will result in "sample_4" as the ID.

4. When the command finishes, examine the content of MY_OUTPUT directory::

	cd MY_OUTPUT
	ls

The layout of the output directory is::

MY_OUTPUT/
          metafile/
                   manifest.tsv
          analysis/
                   SAMPLE-1/
                   SAMPLE-2/
                   ...
          joint/
                vcfs/

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Introduction to DADA2-based MicroHaplotype software

Introduction to Microhaplotype based analysis COMING SOON. This pipeline contains a wrapper for the MIT-Broad team DADA2 software. (https://github.com/broadinstitute/malaria-amplicon-pipeline)

Quick Tutorial

Prepare pipeline install, analysis directory and raw data as above.

1. Execute the ngs-pl run-full-analysis command with as follow::

	ngs-pl run-full-analysis -o outdir test-data/*.fastq.gz

2. When the command finishes, examine the content of outdir directory

    outdir/
            alignments/
                marker_1.fasta
                marker_1.msa
                marker_2.fasta
                marker_2.msa
                ...
            trimmed/
                sample_1_R1.trimmed.fastq.gz
                sample_1_R2.trimmed.fastq.gz
                ...
            malamp/
                dada2/
                    ...
                ASVSeqs.fasta
                ASVTable.txt
                asv_to_cigar
                outputCIGAR.tsv
                meta

The primary output file of interest is the outputCIGAR.tsv which contains the haplotype and their frequencies across the samples.

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