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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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Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM -
With the launch of new single-cell sequencing platforms in 2026, the field stands at an exciting inflection point. This article surveys the most impactful advances in the field and discusses how they’re reshaping research in cancer, immunology, and beyond.
Introduction
Single-cell sequencing technologies have undergone remarkable advances over the past decade, transitioning from low-throughput experimental approaches to highly scalable platforms capable of...05-22-2026, 06:42 AM
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