Comparison And Evaluation Of Read Mapping

Question

[Medhat]

There is a nice tools called ARDEN (artificial reference driven estimation of false positives in next-generation sequencing data) which is:

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a novel benchmark method that estimates error rates of read mappers based on real experimental reads, using an additionally generated artificial reference genome. It allows a dataset-specific computation of error rates and the construction of a receiver operating characteristic curve. Thereby, it can be used for optimization of parameters for read mappers, selection of read mappers for a specific problem or for filtering alignments based on quality estimation.

but I have some problems with It. do any body knows if there is a similar tools to it do the same functions?

Answer 1

[DG]

Not exactly the same thing but GCAT might be a useful resource. It isn't simulated data. Instead they took some real datasets and you can benchmark and upload analysis pipelines for both mapping quality and variant calling. Various read lengths and sequencing platform data are all available for genomes and exomes from the same reference individual. The famous "most sequenced genome in the world"