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Yeah, we were quite surprised when I spoke to them and discovered this. In the future we might ask them to use all and increase the cycles to 14 or 15. That would explain A LOT of reasons why we are struggling with our samples (RNA, not so much for DNA).
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Hi jteeee2,
I just wanted to check back in with you and say thank you. We did some testing in the lab and both the primers / Taq you recommended appeared to work well. We submitted that to our Sequencing CORE and we were able to save over 2/3's of those 68 samples. That a huge relief!!! So instead of all 4 out of 72, we now have material for 49. We have a plan to save those other 23 samples and we are asking them to increase the cycles from 12 for future RNA/FFPE runs.
Thank you so much.
SueComment
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Glad to hear things are improving. Best of luck getting those last 23 samples made into libraries.Comment
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Love 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.07-01-2026, 11:43 AM
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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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