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Started by Dr Drew, 05-08-2008, 01:54 PM
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by cgb
05-09-2008, 12:38 AM
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Started by ScottC, 05-07-2008, 03:14 PM
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by ScottC
05-07-2008, 03:14 PM
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Started by ECO, 04-22-2008, 09:02 PM
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21 responses
12,303 views
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by ScottC
04-30-2008, 06:57 PM
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Started by ECO, 02-27-2008, 09:26 AM
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3 responses
5,190 views
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by ECO
04-23-2008, 02:41 PM
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Started by todd, 04-14-2008, 05:26 AM
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1 response
3,981 views
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by ECO
04-14-2008, 09:14 AM
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Started by DNAcowboy, 04-09-2008, 12:20 AM
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2 responses
4,741 views
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by DNAcowboy
04-09-2008, 10:11 PM
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Started by eldfors, 04-04-2008, 07:39 AM
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3,576 views
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by eldfors
04-04-2008, 07:39 AM
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Started by lgoff, 02-20-2008, 07:22 AM
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3,069 views
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by lgoff
02-20-2008, 07:22 AM
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Started by chrisdag, 01-23-2008, 01:33 PM
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3,618 views
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by chrisdag
01-23-2008, 01:33 PM
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Started by ECO, 01-21-2008, 10:11 PM
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1 response
3,778 views
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by chrisdag
01-23-2008, 01:04 PM
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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, 07-02-2026, 11:08 AM
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18 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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19 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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21 views
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by SEQadmin2
06-26-2026, 11:10 AM
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