borealis

Borealis performs outlier analysis for count-based bisulfite sequencing data to detect outlier methylated CpG sites from bisulfite sequencing (BS-seq) for rare disease diagnoses.

Key Features:

• Beta-Binomial modeling: The core of Borealis uses a beta binomial model to identify outlier methylation.
• Single CpG site resolution: Borealis identifies outlier methylation at single CpG site resolution from bisulfite sequencing data.
• Heterogeneous cohort analysis: Borealis detects aberrantly methylated sites as outliers from a heterogeneous cohort of individuals, addressing a need unmet by standard differential methylation analyses based on case-control groups.

Scientific Applications:

• Rare disease diagnosis: Borealis can successfully identify outlier methylation linked to phenotypically relevant genes in rare disease patients undiagnosed following DNA-based testing, providing a new avenue for increased diagnostic rates.
• Genomic imprinting disorder investigation: Borealis enables systematic application of genome-wide methylation-based sequencing for undiagnosed cases of rare disease involving disorders of genomic imprinting and aberrant DNA methylation.

Methodology:

Borealis is implemented in R and uses a beta binomial model to identify outlier methylation at single CpG site resolution from count-based bisulfite sequencing data.