Package: methylcheck
methylcheckis a Python-based package for filtering and visualizing Illumina methylation array data. The focus is on quality control. View onReadTheDocs.methylcheck is part of the methylsuitemethylcheckis part of themethylsuiteof 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). This package is focused on quality control for processed methylation data.methylcheckfunctions are designed to work with a minimum of knowledge and specification required. But you can always override the "smart" defaults with custom settings if the default settings don't work for your data. The entiremethylsuiteis designed in this format: to offer ease of use while still maintaining flexibility for customization as needed.Methylsuite package componentsYou should install all three components, as they work together. The parts include:methylprep: for processingidatfiles or downloading GEO datasets from NIH. Processing steps includeinfer type-I channel switchNOOB (normal-exponential convolution on out-of-band probe data)poobah (p-value with out-of-band array hybridization, for filtering low 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 matrixlarge batch memory management, by splitting it up into smaller batches during processingmethylcheck: (this package) for quality control (QC) and analysis, includingfunctions for filtering out unreliable probes, based on the published literatureNote thatmethylprep processwill exclude a set of unreliable probes by default. You can disable that using the --no_quality_mask option from CLI.sample outlier detectionarray level QC plots of staining, bisulfite conversion, hybridization, extension, negative, non-polymorphic, target removal, and specificityspreadsheet summary of control probe performancedata visualization functions based onseabornandmatplotlibgraphic libraries.predict sex of human samples from probesinteractive method for assigning samples to groups, based on array data, in a Jupyter notebookmethylizeprovides more analysis and interpretation functionsdifferentially methylated probe statistics (between treatment and control samples)differentially methylated regions, with gene annotation from the UCSC Human Genome Browservolcano plots (to identify probes that are the most different)manhattan plots (to identify clusters of probes associated with genomic regions that are different)Installationmethylcheckmaintains configuration files for your Python package manager of choice:pipenvorpip. Conda install is coming soon.>>>pipinstallmethylcheckor if you want to install all three packages at once (recommended):>>>pipinstallmethylsuiteTutorials and GuidesIf you are new to DNA methylation analysis, we recommend reading through thisintroductionfrom themethylprepdocumentation. Otherwise, you are ready to usemethylcheckto:load processed methylation datafilter unreliable probes from your datarun array-level quality control reportsdetect outlier samplespredict the sex of human samples