# Seeking advice on amount of ambiguity in featureCounts

**URL:** <https://help.galaxyproject.org/t/seeking-advice-on-amount-of-ambiguity-in-featurecounts/2002>\
**Category:** usegalaxy.org support\
**Created:** [August 28, 2019, 9:30pm UTC](https://help.galaxyproject.org/t/seeking-advice-on-amount-of-ambiguity-in-featurecounts/2002 "2019-08-28T21:30:53Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![jennaj](https://sea2.discourse-cdn.com/flex020/user_avatar/help.galaxyproject.org/jennaj/32/27_2.png) [@jennaj](https://help.galaxyproject.org/u/jennaj)\
**Post date:** [August 28, 2019, 10:48pm UTC](https://help.galaxyproject.org/t/seeking-advice-on-amount-of-ambiguity-in-featurecounts/2002/2 "2019-08-28T22:48:25Z")

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Welcome @NitDawg

Your read data appears to have high duplication. If you run `FastQC` you’ll find more details/confirmation about read duplication in those reports.

QA won’t help if the source data actually has high redundancy (tool: Trimmomatic). It could just be low-quality sequencing results or very deep sequencing was done. Contamination could be a factor, but removing those reads won’t help to get more data assigned to a known gene from your reference annotation, it will just reduce the final number of “unassigned-ambiguity” later on in the pipeline.

One note: It is import to run `HISAT2` with the option to output results that are formatted for `Stringtie`. That is covered in the tutorial but is sometimes missed. Worth double-checking. Use the “rerun” (double circle icon) for the mapping jobs to review what options you used.

More DE analysis tutorials can be found here under the group “Transcriptomics” if you want to compare methods/tool choices:

- [Troubleshooting resources for errors or unexpected results](https://help.galaxyproject.org/t/troubleshooting-resources-for-errors-or-unexpected-results/42)

> [@Troubleshooting resources for errors or unexpected results](https://help.galaxyproject.org/t/troubleshooting-resources-for-errors-or-unexpected-results/42/1):
>
> [Galaxy Training Network Tutorials](https://galaxyproject.github.io/training-material/): Some [GTN](https://galaxyproject.org/teach/gtn/) tutorials are appropriate for [Galaxy Main](https://usegalaxy.org) and some are not. Where you can run each is noted per tutorial – click on the _Galaxy instances_ gear icon ![galaxyserversGTN](https://us1.discourse-cdn.com/flex020/uploads/galaxy/original/1X/1287f50cfcdaa1aad750fe323f96995260ac4947.png) to review the [Public Galaxy](https://galaxyproject.org/use/) server choices. If a tutorial is supported by a pre-configured [Galaxy Docker](https://hub.docker.com/r/bgruening/galaxy-stable/) training image, instructions for how to get it will be listed below the tutorial listings, per category.

Hope that helps!

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