HISAT2 alignment results in very low in number of mapped reads

Hi all
I am trying to analyse my mRNAseq data using the galaxy reference based workflow (Reference-based RNA-Seq data analysis). I am very new to data analysis and also to galaxy. I tried two different approaches to align my data:
1)RNA-STAR followed by feature counts: In this case the feature counts showed 0 counts.
2) Next, I tried HISAT2 alignment…and that showed just 177 reads…

I don’t understand why the read number is so low…do you have any suggestions?

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Hi @poojamuk19,
which reference genome and annotation file are you using?

Regards

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Hi @gallardoalba
I have same problem. just few reads align to ref genome. my organism`s ref genome is not supported by galaxy. So, I uploaded fasta file to the history then did alignment using hisat2 and star too. i download fasta and gtf file from here. Index of /genomes/refseq/bacteria/Streptomyces_coelicolor/latest_assembly_versions
After quality control (trimming) the reads are 32 bp and it is ribo seq data.

Many thanks

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Hi @pshtiwan_babane

Check to make sure that your inputs are correctly formatted, are a match with each other, and tool parameters that make use of attributes in the GTF are actually present in your GTF dataset. You may also need to do some more QA on your reads.

FAQs: Galaxy Support

GTN Tutorials: https://training.galaxyproject.org

  • Many tutorials cover read QA/QC steps specific to different analysis goals/tools
  • This one is a good place to start for basics: NGS data logistics

I also added a few tags to your topic that link to prior Q&A that cover the above items in the context of other people’s analysis.

Thanks!

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hi @gallardoalba

I am sorry I can`t do it. must I imported fasta file (ref genome) through ftp or is it ok i uploaded it. then I used NormalizeFasta still doesn’t work!

kindly, can you help me more?

Many thanks

Hi @pshtiwan_babane,
I’ll reproduce the analysis by using that datasets. I’ll inform you as soon as I get some results.

Regards

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Hi @gallardoalba

This will be awesome. Really appreciate your help .