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Christina - Those enrichment numbers seem a little high to me, so I would keep washing. As for my problem, it seemed to work itself out when I went from 5 copies/bead down to 2 copies/bead during amplicon sequencing (did not do a titration).
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Christina85... I am ABSOLUTELY sure it was the pipettor. I have photos and data to support this is a side-by-side experiment we did. We checked everything before hand as well... pcr plate, thermal cyclers, caps for the pcr plates, etc and we had Roche is 3 times. It wasn't until 454 came in with Roche and made this recommendation - now everything works like a dream. And there is correlations between our SVs and LVs (almost perfect). I can send you data / photos if you want to see them. Email me at [email protected].Comment
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One thing I've been doing to increase accuracy (I hope) is perform 2 volume measurements and 2 bead counts for each tube, and then use the averages. Measuring ~1200ul with a pipette is pretty tricky, and I've found that 2 back-to-back measurements, with the same pipette, tip, and user can give differences up to 50ul, and two back-to-back bead counts (using different Accuvettes and different 3ul aliquots) can give differences up to 500,000 beads. Little deviations like these can certainly add up and make troubleshooting difficult, so I'm doing it all in duplicate.Comment
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Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
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Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...07-08-2026, 05:17 AM -
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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