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Best-practice pipelines for fully automated high throughput sequencing analysis

Project description

bcbio-nextgen

A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis. You write a high level configuration file specifying your inputs and analysis parameters. This input drives a parallel run that handles distributed execution, idempotent processing restarts and safe transactional steps. The goal is to provide a shared community resource that handles the data processing component of sequencing analysis, providing researchers with more time to focus on the downstream biology.

Features

  • Community developed: We welcome contributors with the goal of overcoming the biological, algorithmic and computational challenges that face individual developers working on complex pipelines in quickly changing research areas. See our users page for examples of bcbio-nextgen deployments.

  • Installation: A single installer script prepares all third party software, data libraries and system configuration files.

  • Automated validation: Compare variant calls against common reference materials or sample specific SNP arrays to ensure call correctness. Incorporation of multiple approaches for alignment, preparation and variant calling enable unbiased comparisons of algorithms.

  • Distributed: Focus on parallel analysis and scaling to handle large population studies and whole genome analysis. Runs on single multicore computers, in compute clusters using IPython parallel, or on the Amazon cloud. See the parallel documentation for full details.

  • Multiple analysis algorithms: bcbio-nextgen provides configurable variant calling and RNA-seq pipelines.

Quick start

  1. Install bcbio-nextgen with all tool dependencies and data files:

    wget https://raw.github.com/chapmanb/bcbio-nextgen/master/scripts/bcbio_nextgen_install.py
    python bcbio_nextgen_install.py /usr/local/share/bcbio-nextgen --tooldir=/usr/local

producing an editable system configuration file referencing the installed software, data and system information.

  1. Create a sample configuration file with samples from your project (substitute the example BAM and fastq names below with the full path to your sample files):

    bcbio_nextgen.py -w template gatk-variant project1 sample1.bam sample2_1.fq sample2_2.fq
  2. Run analysis, distributed across 8 local cores:

    bcbio_nextgen.py bcbio_sample.yaml -n 8

Documentation

See the full documentation at ReadTheDocs. We welcome enhancements or problem reports using GitHub and discussion on the biovalidation mailing list.

Contributors

License

The code is freely available under the MIT license.

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