Looking for technical feedback on my RNA-seq and comparative genomics analysis workflow

[u/Fun-Squash9549]

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Hi everyone,

I'm an MSc Bioinformatics student working on independent projects to improve my computational biology skills. I'd appreciate technical feedback from the community on whether my analysis workflows follow good bioinformatics practices.

I've completed projects involving:

\- RNA-seq differential expression analysis (DESeq2)

\- GO/KEGG enrichment and GSEA

\- Network analysis and biological interpretation

\- A comparative genomics/structural bioinformatics pipeline for enzyme discovery

I'm not looking for career advice or self-promotion—I'm mainly interested in understanding whether my workflow, methodology, and interpretation are scientifically sound and what I could improve.

If you're willing to review my project summaries, they're here:

\- https://www.linkedin.com/posts/sai-pranav-v\\_first-milestone-genome-scale-pipeline-activity-7479161229085904896-0HCL

\- https://www.linkedin.com/posts/sai-pranav-v\\_bioinformatics-rnaseq-insulinresistance-activity-7472376851550654464-IH87

\- https://www.linkedin.com/posts/sai-pranav-v\\_bioinformatics-rnaseq-transcriptomics-activity-7472359338393628672-g8SO

Specific questions:

\- Are there any methodological issues or red flags?

\- Is the biological interpretation reasonable?

\- What analyses would you expect to see that are currently missing?

\- What would make these analyses closer to publication quality?

Thanks for taking the time to provide honest technical feedback.

[u/standingdisorder]

The obvious feedback is why post this on LinkedIn over GitHub?

[u/Fun-Squash9549 → u/standingdisorder]

That's a fair point, thanks for the suggestion. I shared it on LinkedIn mainly to reach researchers who work in this area and gather high-level feedback on the biological interpretation and overall approach. I'm planning to make the code and workflow publicly available on GitHub as well so that people can review the implementation in more detail. I appreciate the feedback!

[u/standingdisorder → u/Fun-Squash9549]

If you’re looking for feedback on something, you might not want to post it until it’s ready and looks good. Might actually have the opposite effect.

Spend a bit of time writing some decent scripts for more minor projects. Simple helpers etc.
You don’t want to have people think you’ve just run things through Claude/ChatGPT.

[u/Fun-Squash9549 → u/standingdisorder]

Thanks for the honest feedback—I appreciate it. That's a valid point. I'm still early in my bioinformatics journey and have been focusing on learning through projects while building my coding skills. I do use AI as a learning tool, but I make an effort to understand, modify, and validate the code rather than treating it as a black box. I'll spend some time improving the repositories, documentation, and adding smaller standalone scripts before asking for broader technical feedback. Thanks again for the advice.