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Aligned to mm10 using bowtie2, and converted to a sorted bam using samtools. How do I analyze my reads and what transcripts they correspond to
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I'd drop the bowtie2 and instead use Tophat2 (which granted, will use bowtie2 internally but will also do better analysis). -
or Mira or NewblerComment
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I had a question about that. Does bowtie2 throw reads out if they overlap at a splice junction since you're referencing to a genome ?Originally posted by westerman View PostComment
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Depends on what command line parameters you use. Within some limitations ' --local' will map the read to either side of the splice but you will have to force the program to show more than the 'best' alignment via '-k' or '-a'.Originally posted by KnowNothing2 View Post
I point out that Tophat2 does not use '--local' but rather '--end-to-end'. It can do this because it actually splits up reads into smaller segments that should map end-to-end and not need the soft-clipping that 'local' generates.Comment
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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...06-18-2026, 07:11 AM -
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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