To be honest, I'm just giving it a try. I'm not sure what is the alternative step...
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How can I trim this data using Trimmomatic?
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It seems to me that the base call is not really good, you're getting close percentages of at least two bases per bin. Do you think this can be improved by trimming? If data comes from the study Jack Tierney mentions, you're working with RNA seq data, I'm pretty positive it shouldn't look like this.
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Hey Alvesha,
Maybe before asking whether you can or cannot trim your data with Trimmomatic, you should ask yourself why are you trying to trim, what is it that you don't trust in this sequence and then you can pick one (or more) of the Trimmomatic functions. TL;DR: Yes, you can basically force trim with Trimmomatic but you shold make sure that's what you need
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Hey, the
HEADCROPstep option could be what you are looking for. See the Github for details: https://github.com/usadellab/TrimmomaticHey, I have tried but to no avail. I'm not sure what's wrong.. :(
What kind of data is this? Looks like some kind of amplicons/PCR products. Are you sure trimming is needed and if it is then you will know what you need to trim.
The accession suggests the data comes from this study. Just out of interest, what features of the plot make it look like it may be amplicons/PCR products? I'd love to get better at diagnosing issues from FASTQC reports
Being able to (almost) read the sequence by looking at the plot. It is a human gut metagenome sample. Not sure why it is labeled RNAseq.
Hi, you're right! In this study, bacterial 16S ribosomal RNA (rRNA) gene sequencing is performed on DNA isolated from fecal samples in order to characterize the gut microbial communities in individuals.
You may already be planning to but use proper software like Qiime2 to do this analysis: http://qiime.org/tutorials/
Thanks for the information!
This is the metagenomic data extracted from the study "Gut microbiome alterations in Alzheimer’s disease" in NCBI BioProject.