BEAR is the viral diagnostic pipeline, currently designed for SARS-Cov-2. The pipeline takes as input paired-end sequencing reads and creates as output a PDF with the result of the test for the virus (positive or negative). The PDF also includes other qualitative and quantitative measures, detailed below.

The pipeline first aligns the reads to a database of betacoronaviruses (performed in parallel). Separately, it creates contigs from the reads. This contigged assembly is then pairwise aligned to SARS-CoV-2.

The Breadth of coverage statistics and coverage data are gathered after alignment is complete. Custom Python code creates a dotplot showing the quality of the de novo assembly to the match viral genome (SARS-CoV-2), breadth of coverage, and bar plots indicating the breadth of coverage percentage of the reads to the database of related viral genomes.

• Installation
  • Install BEAR and dependencies manually
  • Install BEAR using Conda
• Running
  • Run BEAR with Docker
  • Run BEAR on a single machine
  • Run BEAR on SLURM
• Detailed Guide
  • Usage and options
  • Setup and output folders
• Publications
• Contributing

The BEAR pipeline and all its dependencies are Linux based. There are several options for installation, detailed below. The BEAR pipeline contains a test dataset that can be used to verify instillation.

You can install the BEAR pipeline and all its dependencies manually.

1. Install the dependencies manually:

   • BWA
   • Samtools
   • Minimap2
   • MEGAHIT
   • SciPy
   • Argparse
   • Python
   • Numpy
   • Matplotlib
   • Pandas

2. Clone or download the repository from Github

git clone https://github.com/aidenlab/BEAR.git
cd ./BEAR/Library001 && ../align_serial.sh

or

curl -sSL -o BEAR.zip https://github.com/aidenlab/BEAR/archive/master.zip
unzip BEAR.zip && mv BEAR-master BEAR && rm BEAR.zip
cd ./BEAR/Library001 && ../align_serial.sh

3. Run the provided test dataset to check instillation

cd ./BEAR/Library001 && ../align_serial.sh

You can install the BEAR pipeline and all its dependencies using Conda.

1. If not already done, install Conda.

2. Clone or download the BEAR pipeline.

git clone https://github.com/aidenlab/BEAR.git

3. Create the conda environment.

conda env create -n bear_conda_env -f ./BEAR/bear_conda_env.yml

4. Activate the conda environment and run the provided test dataset to check instillation.

conda activate bear_conda_env    
cd ./BEAR/test && ../align_serial.sh
conda deactivate

The BEAR pipeline is typically run on a Linux operating system, preferably (but not necessarily) on a computer cluster. The included test dataset can run on a laptop in under 5 minutes

Running the BEAR pipeline with the provided test using Docker

docker run --rm aidenlab/polar:latest -d /tmp/test

1. Ensure you have installed the required dependencies.
2. Clone repository.

git clone https://github.com/aidenlab/BEAR.git

3. Modify the variables at the top of align_slurm.sh to correspond to your system's load, commands, and queues. Systems vary in their resources, but we have tried our best to make it easy to modify the SLURM script to fit your system. Modify the variables at the top of the script to work with your system. For example, you can modify "LOAD_BWA" so that it loads the appropriate module or exports the right path. You can also change the call "BWA_CMD" to be the full path to the executable.

4. Run the provided test dataset to check instillation.

cd ./BEAR/test && ../align_slurm.sh

1. Ensure you have installed the required dependencies.
2. Clone repository.

git clone https://github.com/aidenlab/BEAR.git

3. Run the provided test dataset to check instillation.

cd ./BEAR/test && ../align_serial.sh

Usage: align_serial.sh [-d TOP_DIR] [-t THREADS] -jkrh
* [TOP_DIR] is the top level directory (default: "/Users/per/Documents/GitHub/BEAR/test")
        Note: [TOP_DIR]/fastq must contain the fastq files
* [THREADS] is number of threads for BWA alignment (default: "4")
* -r Only align to SARS-CoV-2
* -k Run specific stage of pipeline
* -h Print this help and exit

For debugging, you can have the pipeline create indices of the aligned bam files; pass in the -j flag to enable this option.

For quicker processing, you can choose to align to a reduced set that includes only the "match" and "close" genomes; pass in the -r flag to enable this option.

Send in the number of threads you wish to use for BWA alignment via -t threads.

Place the paired-end sequenced reads in a folder labeled fastq. For example, if your experiment is called "Library001", you should have a folder labeled "Library001," and it should contain one subfolder labeled "fastq" with the fastq files in it. The fastqs can be zipped or unzipped, and there can be multiple pairs. This directory structure is shown below in the form of a tree structure.

Library001
└── fastq
    ├── library001_R1.fastq.gz
    └── library001_R2.fastq.gz

The pipeline will create an "alignments" folder, an "assembly" folder and a "final" folder under "Library001." The "alignments" folder will contain alignments and log files of the data to all the references files. The "assembly" folder will contain the assembly data and log files. The "final" folder will contain the assembly fasta and the final PDF report.

Library001
├── alignments
│   ├── MERS
│   ├── SARS
│   ├── SARS-CoV-2
│   │   ├── aligned
│   │   └── debug
│   └── stats.csv
├── assembly
│   ├── debug
│   │   ├── contig.out
│   │   ├── dotplot.out
│   │   └── paf.out
│   └── work
│       ├── checkpoints.txt
│       ├── contig.paf
│       ├── done
│       ├── intermediate_contigs
│       ├── log
│       └── options.json
├── fastq
│   ├── library001_R1.fastq.gz
│   └── library001_R2.fastq.gz
└── final
    ├── final.contigs.fa
    └── report.pdf

Below are examples of a positive report (A) and a negative report (B).

• St Hilaire BG, Durand NC, Mitra N, Pulido SG, Mahajan R, Blackburn A, et al. A rapid, low cost, and highly sensitive SARS-CoV-2 diagnostic based on whole genome sequencing. bioRxiv. 2020. https://doi:10.1101/2020.04.25.061499

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