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Started by ECO, 11-21-2011, 08:25 PM
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16 responses
55,148 views
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by plant_hunt
11-06-2019, 05:43 AM
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Started by Isabela, 08-03-2016, 11:52 PM
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1,233 views
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by Isabela
08-03-2016, 11:52 PM
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Started by rajesh mahato, 08-01-2016, 03:19 AM
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Started by sanjeevksh, 05-13-2016, 03:59 PM
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5 responses
3,185 views
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by sanjeevksh
07-30-2016, 02:56 AM
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Started by faikceylan, 07-29-2016, 12:33 AM
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1,063 views
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by faikceylan
07-29-2016, 12:33 AM
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Started by taccycle, 07-14-2016, 12:22 AM
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1,107 views
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by taccycle
07-14-2016, 12:22 AM
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Started by Seraficus, 07-12-2016, 03:49 AM
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by Seraficus
07-12-2016, 03:49 AM
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Started by Ikay, 07-11-2016, 05:08 PM
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1 response
1,156 views
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Started by Joann, 07-07-2016, 03:51 AM
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by Joann
07-07-2016, 03:51 AM
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Started by vanw0001, 04-09-2011, 06:53 AM
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7 responses
3,146 views
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by Joann
07-07-2016, 03:41 AM
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Started by dr63, 07-05-2016, 12:31 AM
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2 responses
1,342 views
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by dr63
07-05-2016, 04:24 AM
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by SEQadmin2
Childhood cancers, effectively fatal 60 years ago, are now curable for up to 85% of children with access to contemporary treatments and...-
Channel: Webinar Series
05-08-2026, 01:42 AM -
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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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Channel: Articles
06-02-2026, 10:05 AM -
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Started by SEQadmin2, Yesterday, 11:08 AM
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by SEQadmin2
Yesterday, 11:08 AM
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Started by SEQadmin2, 06-30-2026, 05:37 AM
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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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by SEQadmin2
06-26-2026, 11:10 AM
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