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My lab has been using the Agilent 50Mb SureSelect Human All Exon kit for many months now. Though the data is acceptable, we can’t help but wonder why our coverage plots look so different from Agilent coverage plots. (see attachment) Do other users produce data that results in coverage plots similar to those advertised by Agilent? If so, do you have any suggestions as to why we are seeing this disparity? Or, are our results the accepted norm?
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Last edited by SMO; 05-02-2011, 11:33 AM. -
How are you sequencing it? GAIIX, HiSeq, SOLdD etc? Barcoded? If so, how many exomes per lane? -
These were ran on HiSeq 2000, and were not indexed.Comment
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What are you seeing for percent on target?Comment
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Also, we are getting an average of 80 million reads for a PE 2x101.Comment
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Your curves are consistent with what I see when running Agilent 50M SureSelect with paired 100bp reads.
Not sure what this "Agilent's data" curve you're showing is, but it may be due to any number of things--library prep, Agilent likely used paired 76bp reads (which they recommend), et cetera.Mendelian Disorder: A blogshare of random useful information for general public consumption. [Blog]
Breakway: A Program to Identify Structural Variations in Genomic Data [Website] [Forum Post]
Projects: U87MG whole genome sequence [Website] [Paper]Comment
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Thanks for the input.
Do you see similar coverage plots for Agilent mouse?
We have noticed that the curves for mouse differ greatly from human, using the same protocol, reagents and technicians. See attachment.Comment
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I don't understand the Y-axis here. What are you calling "the exome"?
Haven't done Mouse myself. But again, I would not fret over this.
The Sureselect 50M performance is still high over its targets regardless.
Mendelian Disorder: A blogshare of random useful information for general public consumption. [Blog]
Breakway: A Program to Identify Structural Variations in Genomic Data [Website] [Forum Post]
Projects: U87MG whole genome sequence [Website] [Paper]Comment
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Script
Hi,Originally posted by SMO View Post
could you provide the script, with which you have generated the plot shown in "human coverage plot.pdf" ?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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