Originally posted by gringer
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It shows that PCR-free libraries can hide a larger amount of adapters and adapter dimers somehow entangled in the y-adapters. We have several times seen surprises with (on the BA) clean looking PCR-free libraries in this regard.
Originally posted by gringer View Post1.5% index hopping with no adapters spiked in. Does that mean anything?
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I wonder if there is any update on this.Originally posted by ECO View PostAnyone doing significant multiplexing should be using dual indicies, which reduces this problem dramatically (making swapped reads go to Undetermined while demultiplexing).
Interested to see if this is a problem in our novaseq runs...will update if I note something.
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In our core we did the following test: Project with 64 RNA-Seq libraries prepared using Illumina TruSeq Stranded mRNA HT Dual Index kit on a Perkin Elmer Sciclone G3 robot. We also add a second AMPureXP cleanup at the end of the prep. We divided these into 8 pools of 8 libraries each following the dual index pooling guidelines in Illumina's white paper about index hoping so that each pool had 8 dual-unique index pairs. Each pool was loaded on one lane of HiSeq 4K flow cell and sequenced SE50 (51 cycles R1, 8 cycles I1, 8 cycles I2) using standard protocol.Originally posted by nucacidhunter View PostI wonder if there is any update on this.
Total output per lane was ~370-380M reads. With 8 i7 and 8 i5 indexes in each lane there are a total of 64 combinations possible, 8 expected combinations and 56 which may result from index hoping. I ran bcl2fastq (2.19.0) looking for all index pairs, permitting 1 mismatch per barcode.
For any given unexpected index pair produced through index hoping I found an average of ~35,000 (± 9,850) reads or approximately 0.01% of the total lane output.
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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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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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