Whole Genome Methylation Sequencing Analysis. WGBS is a preeminent technique for exploring the methylome - the comprehensive methylation status of an entire genome. This method holds immense significance in unraveling the epigenetic intricacies of genomes. This approach offers unprecedented insights into gene expression regulation, developmental processes, and disease mechanisms by comprehensively probing methylation patterns across the entire genome. Through WGBS, researchers can identify vital regulatory regions and potential biomarkers. The technique's ability to unveil epigenetic alterations associated with diseases, such as cancer, paves the way for innovative diagnostic and therapeutic strategies.
The technical analysis involves a sequence of systematic steps, contributing to a thorough comprehension of genomic dynamics. Optionally, a Reference Genome Index can be established using Bismark, serving as a foundational base for subsequent actions. Rigorous quality assessment through FastQC ensures data reliability from the start.
Refining data includes adapter sequence trimming through "Trim Galore!". Read alignment is executed using Bismark, then eliminating duplicate alignments to enhance data purity. Subsequent extraction of methylation data and generating Sample and Summary Reports using Bismark exemplify a comprehensive analytical approach.
Evaluation extends to Alignment QC executed via Qualimap, confirming alignment accuracy. The complexity of samples is assessed using the Preseq method.
Importance of Quality Control and Bias Evaluation in Methylation Sequencing Analysis:
Ensuring trustworthy results in methylation sequencing analysis demands stringent quality control. A significant challenge arises during library construction, notably in Bisulfite sequencing samples. Steps like end-repair introduce bias, impacting accurate methylation assessment. The "m-bias" plot can illuminate this bias, a visual tool exposing a telltale pattern: specific cytosines, filled during end-repair, lead to incorrect interpretations. Read 2's bias, caused by these altered cytosines, calls for meticulous bias assessment through m-bias plots to ensure reliable findings.
Additional plots and reports to help you better understand the analysis results, including methylation distribution across the genome, Genomic viewer files, Coverage plots, insert size report, and mapping quality.
Results and output files:
Files:
Deduplicated aligned reads (BAM files)
M-bias reports
BED-graph files
Methylation calls and coverage
Plots:
M-bais plots
Methylation distribution
QC plots
Coverage
Reports:
Qualimap reprots
Bismark reports
Analysis summary reports and slides
Technical report with list of tools and versions
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