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Has anyone done RNA-Seq with reads that failed chastity test? When we sequence, we get a export file and fastq file back from Illumina. The export file usually has a few million reads extra that failed chastity and never made it into the fastq file. In one of our samples, 75% of the reads failed chastity. I assume it is safe to use these reads during mapping? If they are truly bad reads, they shouldn't map. Or does anyone disagree???
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First things first, if you I had 75% failed reads I would call that a failed run and request a re-run from your service provider.Originally posted by blindtiger454 View Post
Can you use the failed reads? Sure, you can but is it wise to do so. What is your experiment? If you are strictly doing expression analysis, that is counting fragments aligned to transcription units then you could probably get away with it. On the other hand if you are interested in identifying variations (e.g. SNPs) then I would not use failed reads. They would produce too many false positives. In fact if you are using your sequence data for variant discovery you should go beyond the Illumina chastity filters, cleaning up the reads even further.
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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...Today, 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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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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