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The authors who publish an aligner are often required to compare and contrast with existing tools. So you can reads the papers associated with aligners of interest and see if the authors convince you to use their aligner. Of course, the authors have an unavoidable bias towards their own aligner in this scenario.
A number of bloggers have discussed the question informally online. For example:
This month I’ve come across some interesting statistics on the performance of Maq, Eland, and other short-read alignment tools as applied to Illumina/Solexa data. I took note because these pr…
Ideally, there would be a paper(s) written by a group that did not have their own aligner that did an objective comparison of many aligners. To be most useful, the comparison would be done with different applications in mind. These applications might have different aligner requirements (e.g. mutation discovery, expression profiling, miRNAs, ChIP-Seq, etc.).
I'm not aware of such a publication right now. Maybe someone else is and will post it. Unfortunately, journal editors (and reviewers) seem notoriously merciless towards such manuscripts ... Anything that fits into a 'platform comparison' category is automatically deemed to be less scientifically valuable, not novel, etc. Indeed some journals explicitly ban submission of this type of work.
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by SEQadmin2
I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...-
Channel: Articles
06-18-2026, 07:11 AM -
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by SEQadmin2
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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Channel: Articles
06-02-2026, 10:05 AM -
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06-04-2026, 08:59 AM
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