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@@ -156,15 +156,15 @@ Which could be provided to the pipeline using `-params-file` parameter as shown
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```console
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nextflow run 'https://github.com/TORCH-Consortium/MAGMA' \
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-profile conda_local, server \
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-r v1.1.1 \
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-params-file my_parameters_1.yml
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-profile conda_local, server \
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-r v1.1.1 \
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-params-file my_parameters_1.yml
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```
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# Analysis
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## Running MAGMA using Nextflow Tower
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## Running MAGMA using Nextflow Tower
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You can also use Seqera Platform (aka Nextflow Tower) to run the pipeline on any of the supported cloud platforms and monitoring the pipeline execution.
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@@ -181,11 +181,11 @@ You can run the pipeline using Conda, Mamba or Micromamba package managers to in
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You can find out the location of conda environments using `conda env list`. [Here's](https://docs.conda.io/projects/conda/en/4.6.0/_downloads/52a95608c49671267e40c689e0bc00ca/conda-cheatsheet.pdf) a useful cheatsheet for conda operations.
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You can use the `conda` based setup for the pipeline for running MAGMA
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You can use the `conda` based setup for the pipeline for running MAGMA
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- On a local linux machine(e.g. your laptop or a university server)
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- On an HPC cluster (e.g. SLURM, PBS) in case you don't have access to container systems like Singularity, Podman or Docker
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- On an HPC cluster (e.g. SLURM, PBS) in case you don't have access to container systems like Singularity, Podman or Docker
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All the requisite softwares have been provided as a `conda` recipe (i.e. `yml` files)
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All the requisite softwares have been provided as a `conda` recipe (i.e. `yml` files)
Once the environments are created, you can make use of the pipeline parameter `conda_envs_location` to inform the pipeline of the names and location of the conda envs.
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Next, you need to load the WHO Resistance Catalog within `tb-profiler`; basically the [instructions](https://github.com/TORCH-Consortium/MAGMA/blob/master/conda_envs/setup_conda_envs.sh#L20-L23), which are used to build the necessary containers.
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Next, you need to load the WHO Resistance Catalog within `tb-profiler`; basically the [instructions](https://github.com/TORCH-Consortium/MAGMA/blob/master/conda_envs/setup_conda_envs.sh#L20-L23), which are used to build the necessary containers.
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1. Download [magma_resistance_db_who_v1.zip](https://github.com/TORCH-Consortium/MAGMA/files/14559680/resistance_db_who_v1.zip) and unzip it
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@@ -250,7 +250,7 @@ We provide [two docker containers](https://github.com/orgs/TORCH-Consortium/pack
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> 🚧 **Container build script**: The script used to build these containers is provided [here](./containers/build.sh).
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Although, you don't need to pull the containers manually, but should you need to, you could use the following commands to pull the pre-built and provided containers
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Although, you don't need to pull the containers manually, but should you need to, you could use the following commands to pull the pre-built and provided containers
> :memo: **Have singularity or podman instead?**: <br>
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If you do have access to Singularity or Podman, then owing to their compatibility with Docker, you can still use the provided docker containers.
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Here's the command which should be used
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Here's the command which should be used
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```console
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nextflow run 'https://github.com/torch-consortium/magma' \
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-params-file my_parameters_2.yml \
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-profile docker,pbs \
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-r v1.1.1
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-params-file my_parameters_2.yml \
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-profile docker,pbs \
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-r v1.1.1
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```
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> :bulb: **Hint**: <br>
@@ -307,7 +307,7 @@ errors. Including these is optional, if unknown or irrelevant,
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just fill in with a '1' as shown in example_MAGMA_samplesheet.csv)
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```
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## (Optional) GVCF datasets
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## (Optional) GVCF datasets
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We also provide some reference GVCF files which you could use for specific use-cases.
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```
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use_ref_gvcf = false
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ref_gvcf = "/path/to/FILE.g.vcf.gz"
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ref_gvcf = "/path/to/FILE.g.vcf.gz"
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ref_gvcf_tbi = "/path/to/FILE.g.vcf.gz.tbi"
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```
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@@ -335,7 +335,7 @@ Tim Huepink and Lennert Verboven created an in-depth tutorial of the features of
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We have also included a presentation (in PDF format) of the logic and workflow of the MAGMA pipeline as well as posters that have been presented at conferences. Please refer the [docs](./docs) folder.
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# Interpretation
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# Interpretation
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The results directory produced by MAGMA is as follows:
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└── vcf_files
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```
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## QC Statistics Directory
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## QC Statistics Directory
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In this directory you will find files related to the quality control carried out by the MAGMA pipeline. The structure is as follows:
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- **Phylogeny**
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Contains the outputs of the IQTree phylogenetic tree construction.
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Contains the outputs of the IQTree phylogenetic tree construction.
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> :memo: By default we recommend that you use the **ExDRIncComplex** files as MAGMA was optimized to be able to accurately call positions on the edges of complex regions in the *Mtb* genome
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> :memo: By default we recommend that you use the **ExDRIncComplex** files as MAGMA was optimized to be able to accurately call positions on the edges of complex regions in the *Mtb* genome
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## `vcf_files` Directory
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## `vcf_files` Directory
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```bash
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/path/to/results_dir/vcf_files
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> Unfiltered structural variants detected by the MAGMA pipeline
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## Libraries Directory
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## Libraries Directory
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> Contains files related to FASTQ validation and FASTQC analysis
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> Contains vcf files for major|minor|structural variants for each individual samples
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# Citations
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# Citations
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The MAGMA paper has been published here: https://doi.org/10.1371/journal.pcbi.1011648
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The MAGMA paper has been published here: https://doi.org/10.1371/journal.pcbi.1011648
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The XBS variant calling core was published here: https://doi.org/10.1099%2Fmgen.0.000689
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