{"id":22021688,"url":"https://github.com/lieberinstitute/biocmap","last_synced_at":"2025-03-23T10:20:11.301Z","repository":{"id":113731747,"uuid":"223444482","full_name":"LieberInstitute/BiocMAP","owner":"LieberInstitute","description":"Our typical analysis steps for WGBS data, starting from FASTQ reads and ending with the construction of bsseq objects. 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It consists of two [nextflow](https://www.nextflow.io/)-based \"modules\", which together take a set of FASTQ files, described in [a `samples.manifest` file](http://research.libd.org/BiocMAP/inputs.html#the-samples.manifest-file), and ultimately produce [bsseq](https://www.bioconductor.org/packages/release/bioc/vignettes/bsseq/inst/doc/bsseq.html) R objects containing methylation data and an R data frame of alignment and quality metrics.\n\nThe first BiocMAP module performs speedy alignment to a reference genome by [Arioc](https://github.com/RWilton/Arioc), and requires GPU resources. Methylation extraction and remaining steps are performed in the second module, optionally on a different computing system where GPUs need not be available.\n\n![Workflow Overview](https://github.com/LieberInstitute/BiocMAP/blob/master/workflow.png)\n\n## Features\n\n- GPU-accelerated alignment to a reference genome via [Arioc](https://github.com/RWilton/Arioc)\n- Memory-efficient, HDF5-backed [bsseq](https://www.bioconductor.org/packages/release/bioc/vignettes/bsseq/inst/doc/bsseq.html) output objects immediately ready for analysis with [Bioconductor](https://bioconductor.org/)/R packages of choice\n- Automatic management of [reference files](http://research.libd.org/BiocMAP/annotation.html), allowing simple configuration of [GENCODE](https://www.gencodegenes.org/) release and [other settings](http://research.libd.org/BiocMAP/annotation.html#choosing-build), while alternatively [supporting user-provided files](http://research.libd.org/BiocMAP/annotation.html#custom-annotation)\n- [Support for docker and singularity](http://research.libd.org/BiocMAP/setup-details.html#installation) for flexible and reproducible installation\n- Automatically merge samples split across multiple FASTQ files, using [the `samples.manifest` input](http://research.libd.org/BiocMAP/inputs.html#the-samples.manifest-file)\n\n## Get started\n\n[The BiocMAP documentation website](http://research.libd.org/BiocMAP/index.html) provides a complete description of features, installation, and many other details. To quickly get started, see our [quick-start guide](http://research.libd.org/BiocMAP/quick-start.html).\n\nWe provide [shell scripts](http://research.libd.org/BiocMAP/quick-start.html#your-main-script) for out-of-the-box execution a [SLURM](https://slurm.schedmd.com/overview.html) or [SGE](https://docs.oracle.com/cd/E19279-01/820-3257-12/n1ge.html)-based computing cluster, or for execution on a Linux-based machine. Software dependencies can be installed via the shell script `install_software.sh`, which makes use of docker or Anaconda/Miniconda.\n\n## Authors\n\n[Nick Eagles](https://github.com/Nick-Eagles)\n\n## Cite\n\nWe hope `BiocMAP` will be a useful tool for your research. Please use the following bibtex information to cite this software. Thank you!\n\n```\n@article {Eagles2022.04.20.488947,\n\tauthor = {Eagles, Nicholas J and Wilton, Richard and Jaffe, Andrew E. and Collado-Torres, Leonardo},\n\ttitle = {BiocMAP: A Bioconductor-friendly, GPU-Accelerated Pipeline for Bisulfite-Sequencing Data},\n\tyear = {2022},\n\tdoi = {10.1101/2022.04.20.488947},\n\tpublisher = {Cold Spring Harbor Laboratory},\n\tURL = {https://doi.org/10.1101/2022.04.20.488947},\n\tjournal = {bioRxiv}\n}\n```\n\n## Contact\n\n[Leonardo Collado-Torres](http://lcolladotor.github.io/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flieberinstitute%2Fbiocmap","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flieberinstitute%2Fbiocmap","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flieberinstitute%2Fbiocmap/lists"}