Do these data require trimming/preprocessing?

usegalaxy.org support
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Hi everyone

I’m working with these samples in Galaxy and just generated this MultiQC report. Based on the status checks, I have a few questions:

  1. Do these data require trimming/preprocessing?
  2. Which tool would you recommend for trimming within the Galaxy environment? Should I go with fastp, Trimmomatic, or Cutadapt?

I’d appreciate your insights on the best workflow to clean up these reads before downstream analysis.

Best regards

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Hi,

  1. likely yes
  2. cutadapt is good and very powerful choice with many options. For standard cases there’s nothing wrong with trimmomatic either. fastp is different in that it does QC and trimming in one → it’s particularly useful if you’re repeatedly generating data via the same wetlab protocol and you want to standardize trimming anyway, i.e. you only want to inspect the QC reports afterwards as an extra control step, but you’re not regularly basing your preprocessing decision on the QC outcome.
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“My data consists of RNA-seq reads. Given that both the ‘adapter content’ and ‘per base sequence quality’ metrics are completely green in FastQC, is trimming still necessary?”

“In cases where the quality metrics do not explicitly require trimming, could applying Cutadapt potentially introduce any issues or adverse effects, or is it considered a safe practice?”