methylbase-object-handling

methylbase-object-handling

Summary

Create and manipulate methylBase objects in methylKit by merging methylRaw samples across common genomic bases and applying coverage filters to ensure consistent sample representation for downstream differential methylation analysis. methylBase objects are the core data structure that enable comparative and statistical analysis across replicate bisulfite sequencing experiments.

When to use

After reading in per-sample methylation call files with methRead() and obtaining methylRawList objects, but before calculating differential methylation or performing annotation. Use this skill when you have multiple bisulfite sequencing samples and need to restrict analysis to bases covered in all samples to avoid bias from incomplete data.

When NOT to use

• Input is already a methylBase object or other pre-processed comparative methylation object.
• Analysis requires per-sample coverage variation to be preserved (e.g., when sample-level heterogeneity is a key variable).
• Input data are from a single sample only; methylBase is designed for multi-sample comparative analysis.

Inputs

• methylRawList object (output from methRead())
• coverage cutoff parameters (default: min 10X, max 99.9th percentile)

Outputs

• methylBase object with merged sample data
• filtered methylRawList with coverage-corrected samples

How to apply

First, apply filterByCoverage() to each sample in the methylRawList to remove bases with coverage below a quality threshold (default minimum 10X) and discard bases exceeding the 99.9th percentile of coverage in each sample to remove PCR bias artifacts. Then execute the unite() function to merge all filtered samples, creating a methylBase object that contains only base-pair positions covered in all samples. This unified object standardizes the sample representation and prepares data for statistical testing. The resulting methylBase object serves as input to downstream functions like calculateDiffMeth() for differential methylation testing.