EpiScout™ Software Makes Data Analysis Simple
Identifies transcript regions with RNA modifications and calculates their relative abundance. Provides quantitative sample comparisons through integrated spike-in controls.

Genome browser view of the FAM20B gene 3′UTR
over a range of RNA inputs. Sequencing data were trimmed, aligned, deduplicated and split by modification barcode, with separate read tracks for m6A (blue), inosine (red) and the solution control (grey). Enrichment with EpiPlex binders generates peaks indicating the presence of RNA modifications. The bed file marks peak locations as identified by the EpiScout peak caller.

Differential analysis of adenosine methylation
across paired tumor/normal liver tissue RNA. Using a machine learning–trained peak caller and a quantification module that leverages integrated spike-in controls, EpiScout delivers high-confidence differential methylation information, visualized through volcano plots for intuitive sample-to-sample comparison.
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