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Fabulous! Please link to the datasets, and I'll try to put wheels in motion via the wiki :-)
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There is and we have these datasets already. I would be happy to share. We did a number of tests with this dataset for a manuscript we are sending out.
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Simulated reads from real genomes.
We could simulate a range of 'noise' across a series of error models and produce reads characteristic of a variety of technologies... there must be software to do this already right?
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Should we generate data so we have a 'gold standard'? Or just work with metrics based on consistency, speed, and coverage?
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I'd recommend using % reads mapped and the # of reads mapped uniquely as part of the evaluation, and keep in mind that the # of known heterozygotes is a measure of sensitivity, NOT accuracy. My two cents.
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Cool! It shouldn't be too hard either, but we need to have clear guidelines about what to measure and how, so that results are comparable across mappers. The only other thing we need is a dataset and a place to host it...
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Originally posted by dan View PostI was thinking to organize a 'mapathon' on the wiki.... how would you recommend benchmarking accuracy?
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I was thinking to organize a 'mapathon' on the wiki.... how would you recommend benchmarking accuracy?
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HTS Mappers!
Anyone vounteer to update the wiki ;-)
Motivation: A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial.
Results: This survey focuses on classifying mappers through a wide number of characteristics. The goal is to allow practitioners to compare the mappers more easily and find those that are most suitable for their specific problem.
Availability: A regularly updated compendium of mappers can be found at http://wwwdev.ebi.ac.uk/fg/hts_mappe...g/hts_mappers/.
Contact: [email protected]
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by seqadmin
Innovations in next-generation sequencing technologies and techniques are driving more precise and comprehensive exploration of complex biological systems. Current advancements include improved accessibility for long-read sequencing and significant progress in single-cell and 3D genomics. This article explores some of the most impactful developments in the field over the past year.
Long-Read Sequencing
Long-read sequencing has seen remarkable advancements,...-
Channel: Articles
12-02-2024, 01:49 PM -
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