Tweet
In 454 paired-end sequencing analysis (3, 8, or 20kb), has anyone found that the sequence on the left of the linker to be significantly shorter than the sequence on the right? Theoretically, a randomly sheared sample should generate reads with sequences of equal length, on average, on either side of the linker. However, I am seeing a bias for the linker to be located near the start of the read. Could the circular products be more prone to shearing at a site closer to the left side of the linker?
-
-
Your post made me check, but both for the two smaller datasets (bacterial genome 3kb old GS FLX and Titanium 8kb PE), and the larger one (eukaryotic genome Titanium 3kb, 8kb, 20kb) I don't see a significant difference between the length distributions of the left half and the right half.
Also, when I plot the position of the linker (I take the start position of the right half from the 454TrimStatus.txt as a proxy) and divide it by the original trimmed read length, there is no bias either... -
Thanks for checking! I'm curious, how are you shearing after circularization? Covaris or nebulization? Also, are you using carrier DNA? It shouldn't make a difference, I just want to rule anything put...Comment
-
In solexa sequencing, pair end library especially index PE, we also found that pollution of read1 adpter >>read2, i don‘t understand why?Comment
-
BTW, index mate pair library !Comment
-
We follow the standard protocols, so nebulization and carrier DNA.Originally posted by lzembek View PostComment
-
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.Yesterday, 11:43 AM
-
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...
Comment