Has anyone noticed issues with quality scores on amplicon runs since the new version of bcl2fastq came out? I've had a number of runs be questionable since late Oct, but I also changed machines at the same time. Trying to figure out if I need to adjust wetlab conditions to new machine or if it's related to the software update.
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The beginning of R2 qscores are really low. This last run, R1 looks great with ~10% phiX aligned. R2 is horrible, <1% phiX aligned. I'm not sure how this would be software related but the thumbnails look fine-the machine didn't lose focus, clusters are there.
oh hadn't seen that paper, thanks. Haven't used bbmap but know it's on one of our clustersMicrobial ecologist, running a sequencing core. I have lots of strong opinions on how to survey communities, pretty sure some are even correct.
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The qscore profiles look similar to what I was seeing at the beginning of the year. But the machine that I'm currently using is the one that actually lead us to blame the TCM of my old machine
Microbial ecologist, running a sequencing core. I have lots of strong opinions on how to survey communities, pretty sure some are even correct.
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Are you sure the issue is with bcl2fastq? QScores are assigned (binned or not) by RTA. bcl2fastq merely extracts the scores already stored in the BCL file by RTA.Originally posted by thermophile View PostHas anyone noticed issues with quality scores on amplicon runs since the new version of bcl2fastq came out? I've had a number of runs be questionable since late Oct, but I also changed machines at the same time. Trying to figure out if I need to adjust wetlab conditions to new machine or if it's related to the software update.
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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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