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Intro

This is the repository for the paper Gramtools enables multiscale variation analysis with genome graphs.

It is divided into snakemake workflows, one folder each in analysis/workflows.

Setup

Requirements for setup

Input data

Here we list all the datasets used; for each, either public accessions are stored in a file or the data is available for download on Zenodo. We provide scripts and commands to obtain all the data, see below.

Data Access
M. tuberculosis vcfs of 1,017 samples Zenodo
P. falciparum vcfs of 2,498 samples Zenodo
M. tuberculosis validation PacBio assemblies of 17 samples Zenodo
M. tuberculosis validation Illumina read sets of 17 samples ENA accessions listed in analysis/input_data/mtuberculosis/pacb_ilmn/data_accessions.tsv
P. falciparum 14 Illumina read sets and matched PacBio assemblies ENA accessions listed in analysis/input_data/pfalciparum/pacb_ilmn/data_accessions.tsv
P. falciparum 706 Illumina read sets from Pf3k release 5 ENA accessions listed in analysis/input_data/pfalciparum/pf3k/pf3k_release_5.tsv

Steps for setup

All commands work only when issued from the root of this project.

Setup a python virtual environment and obtain snakemake:

    git clone https://github.com/iqbal-lab-org/paper_gramtools_nesting && cd paper_gramtools_nesting
    python3 -m venv venv && . venv/bin/activate
    pip3 install pip==20.0.2 
    pip3 install -r pyrequirements.txt

Obtain the singularity container:

    # Download container:
    mkdir -p container/built && wget https://zenodo.org/record/5075458/files/1_container.sif?download=1 -O container/built/singu.sif
    # It is possible to build the container directly; this should take ~30 minutes:
    # sudo singularity build --no-cleanup container/built/singu.sif container/singu_def.def

Obtain the input data:

    # Some data download uses enaBrowserTools and seqtk, which are installed in container.
    singu_command="singularity exec container/built/singu.sif"

    ## P. falciparum data ##
    "$singu_command" bash analysis/input_data/download_data/pf_dl_ilmn_ena.sh
    "$singu_command" bash analysis/input_data/download_data/pf_dl_pacb_assemblies.sh

    # Below downloads 706 fastqs of ~1GB each; I recommend modifying the script to submit in parallel to a cluster (adding in singularity command too). Downloads from ENA server, several reruns may be required if server throws any error.
    bash analysis/input_data/download_data/pf3k_dl_ilmn_all.sh

    pf_vcfs="analysis/input_data/pfalciparum/pf3k/vcfs"
    mkdir -p "$pf_vcfs"
    wget https://zenodo.org/record/5075458/files/3_pf_vcfs.tar?download=1  -O 3_pf_vcfs.tar
    tar -xf 3_pf_vcfs.tar

    ## M. tuberculosis data ##
    tb_vcfs="analysis/input_data/mtuberculosis/clockwork/vcfs"
    mkdir -p "$tb_vcfs"
    
    wget https://zenodo.org/record/5075458/files/2_mtb_vcfs.tar?download=1 -O 2_mtb_vcfs.tar
    tar -xf 2_mtb_vcfs.tar
    wget https://zenodo.org/record/5075458/files/4_mtb_validation_assemblies.tar?download=1 -O 4_mtb_assemblies.tar
    tar -xf 4_mtb_assemblies.tar

    "$singu_command" python3 analysis/input_data/download_data/mtb_dl_ilmn_ena.py

How to run a workflow

    . venv/bin/activate
    WORKFLOW=<workflow_name>
    # Add -nq to the command below to only preview what would be run.
    snakemake -s analysis/workflows/"${WORKFLOW}"/Snakefile --use-singularity --verbose

We have run the analyses on an LSF Cluster, executing the following:

    . venv/bin/activate
    bash analysis/cluster_submit.sh <workflow_name>

The submission script contains specific filepaths on our cluster which need modifying.

Workflow details

make_prgs

No prerequisites.

In analysis/workflows/make_prgs, at top of Snakefile, there are two configfile: directives, pointing to pfalciparum.yaml and mtuberculosis.yaml. Uncomment the line corresponding to which analysis to run.

Now run :

    bash analysis/cluster_submit.sh make_prgs

This produces inputs required by nestedness_simulations, pacb_ilmn_validation, msps_dimorphism and tb_bigdel workflows.

nestedness_simulations

Requires: make_prgs on pfalciparum.yaml

This produces the results of the section Validation of nested genotyping with simulated data. Because paths in the graphs, and reads from the paths, are randomly simulated, the exact same result will not be produced. I ran the workflow multiple times and got the same performance each time.

pacb_ilmn_validation

Requires: make_prgs on pfalciparum.yaml

This produces the results of the section Validation of nested genotyping with simulated data.

pacb_ilmn_prg_closest_pf

Requires: pacb_ilmn_validation

This produces the results of the section: Comparing gramtools personalised reference with best of reference panel.

tb_bigdel

Requires: make_prgs on mtuberculosis.yaml ; vg_make_prgs

This produces the results of the section: Application: unified SNP and large deletion analysis in M. tuberculosis.

msps_dimorphism

Requires: make_prgs on pfalciparum.yaml

This produces the results of the section: Application: charting SNPs on top of alternate haplotypes.

Development

While working on the paper, it is not convenient as you have to rebuild and transfer the whole container image if anything changes (eg one line in gramtools). For development, it is best to work with a python venv at top-level. Then pip install -r pyrequirements.txt and pip install -r container/pyrequirements.txt. Then locate gramtools on cluster, cmake/make it, and pip install -e it from inside the venv. And in the file analysis/cluster_submit.sh, remove the --use-singularity argument. All tools must be available on cluster.