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Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc
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Started by laura, 05-09-2011, 04:42 AM
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35 responses
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by laura
12-05-2013, 02:37 AM
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Started by sci_guy, 01-23-2008, 11:19 PM
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236 responses
683,010 views
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by ECO
12-25-2009, 06:45 PM
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Started by biocomputer, 05-06-2014, 04:59 PM
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by biocomputer
05-06-2014, 04:59 PM
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Started by southan, 05-06-2014, 03:04 PM
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1,052 views
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by southan
05-06-2014, 03:04 PM
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Started by choijae3, 05-06-2014, 02:06 PM
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1,065 views
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by choijae3
05-06-2014, 02:06 PM
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Started by sowmyai, 05-05-2014, 05:01 PM
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1 response
2,186 views
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by swbarnes2
05-06-2014, 11:13 AM
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Started by krespim, 05-06-2014, 08:17 AM
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by krespim
05-06-2014, 08:17 AM
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Started by ppm, 04-22-2014, 01:47 PM
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4 responses
3,082 views
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by ppm
05-06-2014, 07:49 AM
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Started by greener, 02-22-2011, 03:47 PM
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3 responses
3,886 views
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by jp.
05-06-2014, 05:55 AM
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Started by gevielr, 04-29-2014, 01:20 PM
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2 responses
1,491 views
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by mikep
05-06-2014, 12:45 AM
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Started by Mchicken, 05-05-2014, 11:35 PM
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2 responses
1,882 views
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by Mchicken
05-06-2014, 12:31 AM
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Started by canerb, 05-05-2014, 10:54 AM
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7 responses
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by canerb
05-06-2014, 12:27 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...-
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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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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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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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