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I have a graphic that show an increase in coverge of A over T, and It increses until the end sequence, in all lanes of paired ends runs of 72 pb. Can GAIIx introduce a bias in coverage A on T?
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Yes, for some reason, our recent datasets seem to favour A over T and G over C, when the quality is a bit crappy. We see a rise in N calls roughly correlating this discrepancy.Originally posted by vjimenez View Post
An older dataset (of lower quality) of our is different, with C considerably over G, and T slightly over A.
I don't know if this is an effect from the base-caller or if it's from the adapter sequences, but it's there, around 1% difference. How much of a gap are you seeing?Last edited by tonybolger; 05-18-2011, 04:09 AM. -
The gap between A and T is between 1% to 4% at the end of the sequence. But always in genomic apliaciones of eukaryotes.Veronica Jimenez Jacinto
UUSM.Comment
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Probably nothing too serious - how's the quality at that end?Originally posted by vjimenez View Post
I guess if you're only seeing it in genomic data, it could be related to the specific adapters used.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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