Metadata-Version: 2.1
Name: methylprep
Version: 1.7.1
Summary: Python-based Illumina methylation array preprocessing software
Home-page: https://github.com/FOXOBioScience/methylprep
Author: Life Epigenetics
Author-email: info@FOXOBioScience.com
License: MIT
Project-URL: Documentation, https://life-epigenetics-methylprep.readthedocs-hosted.com/en/latest/
Project-URL: Source, https://github.com/FOXOBioScience/methylprep/
Project-URL: Funding, https://FOXOBioScience.com/
Description: `methylprep` is a python package for processing Illumina methylation array data.
        View on [ReadTheDocs.](https://life-epigenetics-methylprep.readthedocs-hosted.com/en/latest/)
        
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        ## Methylprep is part of the methylsuite
        
        ![](https://raw.githubusercontent.com/FoxoTech/methylprep/master/docs/methyl-suite.png)
        
        `methylprep` is part of the [methylsuite](https://pypi.org/project/methylsuite/) of python packages that provide functions to process and analyze DNA methylation data from Illumina's Infinium arrays (27k, 450k, and EPIC, as well as mouse arrays). The `methylprep` package contains functions for processing raw data files from arrays and downloading/processing public data sets from GEO (the NIH Gene Expression Omnibus database repository), or from ArrayExpress. It contains both a command line interface (CLI) for processing data from local files, and a set of functions for building a custom pipeline in a jupyter notebook or python scripting environment. The aim is to offer a standard process, with flexibility for those who want it.
        
        `methylprep` data processing has also been tested and benchmarked to match the outputs of two popular R packages: [sesame](https://bioconductor.org/packages/release/bioc/html/sesame.html) (v1.10.4) and [minfi](https://bioconductor.org/packages/release/bioc/html/minfi.html) (v1.38).
        
        ## Methylsuite package components
        
        You should install all three components, as they work together. The parts include:
        
        - `methylprep`: (this package) for processing `idat` files or downloading GEO datasets from NIH. Processing steps include
           - infer type-I channel switch
           - NOOB (normal-exponential convolution on out-of-band probe data)
           - poobah (p-value with out-of-band array hybridization, for filtering lose signal-to-noise probes)
           - qualityMask (to exclude historically less reliable probes)
           - nonlinear dye bias correction (AKA signal quantile normalization between red/green channels across a sample)
           - calculate beta-value, m-value, or copy-number matrix
           - large batch memory management, by splitting it up into smaller batches during processing
        
        - `methylcheck`: for quality control (QC) and analysis, including
           - functions for filtering out unreliable probes, based on the published literature
              - Note that `methylprep process` will exclude a set of unreliable probes by default. You can disable that using the --no_quality_mask option from CLI.
           - sample outlier detection
           - array level QC plots, based on Genome Studio functions
           - a python clone of Illumina's Bead Array Controls Reporter software (QC)
           - data visualization functions based on `seaborn` and `matplotlib` graphic libraries.
           - predict sex of human samples from probes
           - interactive method for assigning samples to groups, based on array data, in a Jupyter notebook
        
        - `methylize` provides more analysis and interpretation functions
           - differentially methylated probe statistics (between treatment and control samples)
           - volcano plots (which probes are the most different?)
           - manhattan plots (where in genome are the differences?)
        
        ## Installation
        
        `methylprep` maintains configuration files for your Python package manager of choice: [pipenv](https://pipenv.readthedocs.io/en/latest/) or [pip](https://pip.pypa.io/en/stable/). Conda install is coming soon.
        
        ```shell
        >>> pip install methylprep
        ```
        
        or if you want to install all three packages at once:
        ```shell
        >>> pip install methylsuite
        ```
        
        ## Tutorials and Guides
        If you're new to DNA methylation analysis, we recommend reading through [this introduction](docs/introduction/introduction.md) in order get the background knowledge needed to best utilize `methylprep` effectively. Otherwise, you're ready to use `methylprep` for:
        <br>
        
        - processing [your own methylation data](docs/general_walkthrough.md#processing-your-own-data)
        - downloading [unprocessed data](docs/general_walkthrough.md#downloading-from-geo) (like IDAT files) from GEO.
        - downloading [preprocessed data](docs/special_cases.md#using-beta-bake-for-preprocessed-data) (like beta values) from GEO.
        - building a composite dataset [using control samples](docs/special_cases.md#building-a-composite-dataset-using-meta-data) from GEO.
        - building a composite dataset from GEO data [with any keyword you choose](docs/special_cases.md#building-a-composite-dataset-with-alert-and-composite) (e.g. combining all GEO datasets that have methylation data from patients with brain cancer).
        
        <!-- Add link to methods paper when available -->
        
Keywords: methylation dna data processing epigenetics illumina
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Description-Content-Type: text/markdown
Provides-Extra: dev
