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What are the best methods/programs for attempting to close gaps between scaffolds after a de novo assembly has resulted in a large number of scaffolds (before resorting to further sequencing)?
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First, I don't know why you've chosen to prefix all your posts with your username; not a desirable strategy.
Second, you've failed to describe any details about the genomes you are working on, the data you've acquired & how you've tried to assemble. The size & complexity of the genome are critical to understand as well what you have in hand and what scientific goals you really want to address. -
This series of posts was intended to be topics from a conference/discussion panel to continue discussions here...I should've prefaced it with this before all the posts went up.Comment
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Okay, apologies for the previous comment.
There are a number of scaffolders out there, though I have used only SSPACE and without digging in much.
One thing that would benefit all of these programs is if there was a rigorous language for defining relationships that scaffolding might be based on. Ideally this would a XML; I know many folks aren't XML fans but the value of being able to validate inputs is powerful.
One distinction amongst scaffolders is their modularity. To give two examples, SSPACE is non-modular and must be run en masse. At the other extreme, SGA can apparently be used as a scaffolder & simply takes BAM files and a few parameters.Comment
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I've found that using the following sequence can massively improve contiguity in transcriptome assemblies - the same is likely true for genomes:
1. GapFiller
2. cap3
3. cycle through 1 and 2 again until contiguity gains plateauComment
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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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