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Techniques and protocol discussions on sample preparation, library generation, methods and ideas
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Started by juelraja, 08-26-2013, 05:12 AM
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17 responses
15,900 views
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by Seqasaurus
11-22-2018, 01:06 PM
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Started by paolo.kunder, 12-12-2013, 11:39 PM
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5 responses
9,255 views
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by liuqy
11-20-2018, 11:07 AM
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Started by PrimerBuffalo, 03-20-2017, 08:32 AM
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3 responses
4,108 views
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by Simone78
11-19-2018, 09:08 AM
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Started by GenomeM, 11-13-2018, 06:58 AM
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4 responses
3,416 views
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by GSviral
11-19-2018, 01:19 AM
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Started by Atzin, 10-27-2018, 08:02 PM
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1 response
2,127 views
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by torben
11-14-2018, 03:53 AM
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Started by robicha7, 11-13-2018, 08:57 AM
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0 responses
1,597 views
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by robicha7
11-13-2018, 08:57 AM
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Started by robicha7, 11-12-2018, 08:33 AM
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0 responses
120 views
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by robicha7
11-12-2018, 08:33 AM
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Started by robicha7, 11-12-2018, 07:10 AM
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0 responses
75 views
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by robicha7
11-12-2018, 07:10 AM
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Started by smoics, 11-06-2018, 10:39 AM
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2 responses
1,699 views
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by teuthbrush
11-07-2018, 11:56 AM
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Started by smoics, 11-01-2018, 12:37 PM
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3 responses
2,728 views
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by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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Channel: Articles
07-01-2026, 11:43 AM -
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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
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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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06-02-2026, 10:05 AM -
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Started by SEQadmin2, 07-02-2026, 11:08 AM
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25 views
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by SEQadmin2
07-02-2026, 11:08 AM
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Started by SEQadmin2, 06-30-2026, 05:37 AM
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0 responses
24 views
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by SEQadmin2
06-30-2026, 05:37 AM
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Started by SEQadmin2, 06-26-2026, 11:10 AM
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0 responses
23 views
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by SEQadmin2
06-26-2026, 11:10 AM
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