:orphan: .. only available via index, not via toctree .. title:: Package Recipe 'cfdna-biomarkersearch' .. highlight: bash cfdna-biomarkersearch ===================== .. conda:recipe:: cfdna-biomarkersearch :replaces_section_title: :noindex: Pipeline to identify candidate cfDNA biomarker sequences from WGS data :homepage: https://github.com/avo-hcemm/cfDNA-biomarkers-pipeline :documentation: https://github.com/avo-hcemm/cfDNA-biomarkers-pipeline/blob/master/README.md :license: MIT / MIT :recipe: /`cfdna-biomarkersearch `_/`meta.yaml `_ cfDNA\-BiomarkerDiscovery is a pipeline designed to identify candidate biomarker sequences from cell\-free DNA \(cfDNA\) derived from blood samples. The pipeline takes as input\: • An archive of FASTQ files containing paired\-end reads from whole\-genome sequencing \(WGS\) of one or more case cohorts and a control cohort. • Additional required files\: adapter sequences\, genome version for download\, genome information file\, parameter file\, and an archive with genome FASTA files. The pipeline performs\: 1. Preprocessing\: adapter trimming\, quality filtering\, and alignment to the reference genome. 2. Analysis\: identification of candidate genomic regions as potential biomarkers. If informative regions are identified\, the pipeline generates a CSV file listing the candidate biomarker sequences along with their associated genomic coordinates. .. conda:package:: cfdna-biomarkersearch |downloads_cfdna-biomarkersearch| |docker_cfdna-biomarkersearch| :versions: ``0.1.3-0``,  ``0.1.1-0`` :depends bowtie2: :depends ca-certificates: :depends curl: :depends fastqc: :depends gnupg: :depends imbalanced-learn: :depends multiqc: :depends numpy: :depends openjdk: ``>=21`` :depends pandas: :depends samtools: :depends scikit-bio: :depends scipy: :depends setuptools: ``<81`` :depends sklearn-compat: :depends tar: :depends trimmomatic: :depends unzip: :depends wget: :depends xgboost: :requirements: :additional platforms: .. rubric:: Installation You need a conda-compatible package manager (currently either `micromamba `_, `mamba `_, or `conda `_) and the Bioconda channel already activated (see :ref:`set-up-channels`). While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see `here `_ for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others. Given that you already have a conda environment in which you want to have this package, install with:: mamba install cfdna-biomarkersearch and update with:: mamba update cfdna-biomarkersearch To create a new environment, run:: mamba create --name myenvname cfdna-biomarkersearch with ``myenvname`` being a reasonable name for the environment (see e.g. the `mamba docs `_ for details and further options). Alternatively, use the docker container:: docker pull quay.io/biocontainers/cfdna-biomarkersearch: (see `cfdna-biomarkersearch/tags`_ for valid values for ````) .. |downloads_cfdna-biomarkersearch| image:: https://img.shields.io/conda/dn/bioconda/cfdna-biomarkersearch.svg?style=flat :target: https://anaconda.org/bioconda/cfdna-biomarkersearch :alt: (downloads) .. |docker_cfdna-biomarkersearch| image:: https://quay.io/repository/biocontainers/cfdna-biomarkersearch/status :target: https://quay.io/repository/biocontainers/cfdna-biomarkersearch .. _`cfdna-biomarkersearch/tags`: https://quay.io/repository/biocontainers/cfdna-biomarkersearch?tab=tags .. raw:: html Download stats ----------------- .. raw:: html :file: ../../templates/package_dashboard.html Link to this page ----------------- Render an |install-with-bioconda| badge with the following MarkDown:: [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/cfdna-biomarkersearch/README.html) .. |install-with-bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/cfdna-biomarkersearch/README.html