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Welcome to ARDEN, a method for Artificial Reference Driven Estimation of false positives in NGS.

Introduction

We introduce ARDEN (Artificial Reference Driven Estimation of false positives in NGS data), a novel benchmark that estimates error rates based on real experimental reads and an additionally generated artificial reference genome. It allows the computation of error rates specifically for a dataset and the construction of a ROC-curve. Thereby, it can be used to optimize parameters for read mappers, to select read mappers for a specific problem or also to filter alignments based on quality estimation.

Useful links

[1] FAQ
[2] Installation & Dependencies
[3] Getting started

Project Admins:

• Giese, Sven