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It could also be rRNA; what does the GC plot (per sequence GC content) look like?
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The problem that you describe in the first few bases is often seen with RNA-Seq data,
and is thought to be due to the random priming being not so random in practice.
This has previously been disussed in various threads, one of which is here:
The trimmomatic adapter trimming only trims adapter sequences from the 3' ends of the reads.Comment
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Thanks for all the answers!!! and the link
sarvidsson: The GC plot looks terrible there are 3 peaks in the reads is not a normal distribution.Comment
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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.
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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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