Rat Featurecount Selection

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Welcome @Tapan_Dey

Hopefully we can help!

You are correct that everyone will need to supply reference annotation to tools, including Featurecounts! You will want to obtain annotation that is based on the same reference genome assembly coordinate and labeling system.

The rn6 genome was sourced from UCSC. They also host annotation. To learn where to source UCSC annotation files in their Downloads area, this FAQ can help.

Steps

  1. Start at the UCSC Genome Browser website https://genome.ucsc.edu/. Navigate to their Downloads area, then choose Other Mammals → Rat. The URL of your browser window should be this once you are in the right place.

    https://hgdownload.gi.ucsc.edu/downloads.html#rat

  2. Then go into the assembly you already mapped against (rn6), and navigate down into the /genes directory. The URL should now be this.

    https://hgdownload.gi.ucsc.edu/goldenPath/rn6/bigZips/genes/

  3. Any of the choices are usually fine but one may be a better choice for your goals or downstream analysis plans. Each of the files represents a Gene and Gene Prediction annotation track in the main Genome Browser at UCSC → https://genome.ucsc.edu/. You can inspect these tracks in the main graphical browser or their Table Browser to learn what each represents and how/when/who curated the data.

    The rn6.ncbiRefSeq.gtf.gz data is a common choice!

  4. To get the data into Galaxy: copy the URL for the file, paste it into the Upload tool in Galaxy, leave all settings at default, and the file will uncompress with the correct datatype, ready to use!

  5. On a tool form, choose your newly uploaded GTF dataset from your history.

Please give that a try and let us know if it works or not for you! :slight_smile:

Notes: There are a few ways to label the genome and features, and using the same choice throughout an analysis tends to work best. So, later on, should you notice that counts are not quite what you expected, or an error comes up about “mismatched reference data”, you can inspect your reference data closer and usually find the problem. If you get stuck, you can share the error and the community here can try to help more!

Related topics that can help with additional context about reference-annotation