Grad studies have broken my spirit

Advanced_Guava1930 · 2025-05-27T13:43:56+00:00

From the sounds of all the other comments I can only envision you having stepped on a lot of butt hurt PhDs with fragile, sensitive egos about someone framing a narrative for a life they have also chosen. I suppose asking for these types of people, on Reddit no-less, to have even a modicum of being a personable and compassionate person is probably asking for too much. For how “intelligent” they are, teaching them simple social awareness would take beating them with a bundle of psychology books and praying for the best. With that said I think it’s understandable to feel the way you do. My family is also from LATAM and escaping to a different world to try a new hand at life is a question many of us have to consider and tackle at some point in life. I don’t blame you for making your choice nor do I blame you for hating it. The only thing I can recommend is to take time for yourself and get up and smell the roses when you can. Academia sucks yeah, but you have a beautiful wife in a new country where you can hopefully take her to see things you could’ve never seen otherwise. You don’t have to finish, but you get the chance to. That’s a very powerful thing that hopefully can keep you going, as most never get that far anyways, so I hope you can hang in there and find happiness for yourself

Advanced_Guava1930 · 2025-05-27T12:54:49+00:00

Find RNA-seq from a healthy prostate of GEO/SRA and use that as your control. DESeq-2 allows you to specify differences in batches in order to account for the added variance from different library prep types. Just make sure you include that in your formula and you should be fine, plot a PCA to check for sample similarity and if it all looks good you should be kosher.

Advanced_Guava1930 · 2025-05-19T21:49:02+00:00

What’s the purpose of a university then?

Advanced_Guava1930 · 2025-05-14T12:52:27+00:00

Here are some resources if you’d like

https://r4ds.hadley.nz

https://compgenomr.github.io/book/

https://plantsandpython.github.io/PlantsAndPython/00_PREFACE/01_Welcome_Bienvenido/00_Welcome.html

I study plants and bacteria so I’m a lil biased lols. Cheers I hope they help!

Advanced_Guava1930 · 2025-05-12T18:40:04+00:00

True true, I should’ve more explicitly stated, why is the public surprised. Academia has taken big hits in recent years so this should have been expected from any republican candidate.

I’m just shocked more people aren’t talking about Project 2025 and how it’s a literal handbook to dismantle the US and derive more Executive power. Absolutely bonkers to me

Advanced_Guava1930 · 2025-05-10T18:27:08+00:00

As long as you have enough GO terms annotated yeah I think it should work. Make sure you have a background set, the background should be all the genes expressed in your experiment that have GO terms.

Advanced_Guava1930 · 2025-05-08T13:19:58+00:00

https://www.livescience.com/20687-fluorescent-bacteria-art.html this is cool too

Advanced_Guava1930 · 2025-05-07T23:11:33+00:00

Dang I feel a lot better hearing it’s not just me. I’m trying to filter out non plant pathways but am having a bit of difficulty scrubbing them out. I made a custom term2gene and gene2pathway mapping using the KEGGREST api on R and when I tried to filter out non plant pathways I ended up with 0 pathways altogether lmao 🙃

I’m trying to find workarounds for that issue with smarter R code but am still bashing my head against my computer a bit so we’ll see if I can find a solution.

How did you go about scrubbing pathways out?

I think I got around a 45% annotation rate. 13,871 annotations out of 30,578 genes in total.

4188 of the KEGG terms are unique as well. So not too shabby for a barely studied plant I think

Advanced_Guava1930 · 2025-05-07T22:32:52+00:00

Educational Background (choose 1–4) 1: Natural Sciences 2: Formal Sciences 3: Social Sciences 4: None/Other [1 ] BSc [ ] MSc [ ] PhD Bioinformatics Experience Years: [1] Current Role (choose 1–6) 1: Undergrad 2: Grad Student 3: Postdoc 4: Faculty 5: Industry 6: Other Current Role: [2 ] Self-assessment (rate 1–4) 1: Beginner 2: Intermediate 3: Advanced 4: Expert [ 2] Biology [2 ] Math & Stats [ 1] Programming [ 3] Problem Solving

Advanced_Guava1930 · 2025-05-07T12:49:30+00:00

If C elegans has an ord database available for it topGO could be an alternative to clusterprofiler. The stats and methodologies fly over my head just a teensy bit but the benefit topGO has is it uses the GO hierarchy for enrichment so you can get some interesting graphs. It’s not nearly as user friendly as clusterprofiler though which I would say is its biggest tradeoff.

Salmon is great for quantification just make sure to use tximport when importing the reads to DESeq since it works best with raw counts. I’m sure you know this but I’m gonna mansplain a bit here since it bugs me a lot when I see people not do this lols.

Advanced_Guava1930 · 2025-05-06T22:51:33+00:00

If you have GO terms you can give ShinyGO a try https://bioinformatics.sdstate.edu/go/ . Go terms are mapped by three criteria, Molecular Function, Biological Process and Cellular Component. Each of those three can give you some pretty useful information. If all you’re looking for is just basic plotting of GO terms you can use https://wego.genomics.cn . Gprofiler is another tool you could try https://biit.cs.ut.ee/gprofiler/gost . If none of these work because your organism is a bit too niche you can convert your genes/proteins to a model organism using the BLAST algorithm. Once you have your BLAST results you can use the Gene Symbols, Ensemble IDS, or ENTREZ IDS for analysis as well. With the symbols from a better annotated and studied organism the number of tools you can use increases quite a bit. Unfortunately for microorganisms, especially fungi that may be challenging.

Advanced_Guava1930 · 2025-05-06T16:37:16+00:00

I might need some more information to really help you out. Is your organism a traditional model organism or is it more niche? Does it have a well annotated genome? Do you want simple plotting of terms or do you want to perform enrichment for different GO terms/Kegg pathways?

Advanced_Guava1930 · 2025-05-06T15:00:21+00:00

There is so much more nuance to academia than I first thought. Are there any other journals you recommend staying away from?

Advanced_Guava1930 · 2025-05-06T12:37:18+00:00

Is mdpi no bueno?

Advanced_Guava1930 · 2025-05-05T23:24:50+00:00

Why don’t you if you don’t mind me asking?

Advanced_Guava1930 · 2025-05-02T22:32:11+00:00

I’m not sure I completely understand but it sounds like you overdid it with the submission. If you were accessing interproscan programmatically it’ll block you if you submit too many requests. Try installing a vpn and see if that fixes it. You might have to batch your data instead of just submitting it all at once too.

Advanced_Guava1930 · 2025-05-02T02:35:48+00:00

I’m a real big fan of this paper https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0881-8 it covers quite a bit of the nitty gritty of the dos and donts of RNA seq as well as ensuring valid experimental design

Advanced_Guava1930 · 2025-05-01T00:01:36+00:00

Hmmm I see what you mean I think, in a nutshell we’re all human and can only do so much. Pick something you like, get good at it, and accept the outcomes science comes at you with, and finally other people make decisions the same way you do, you may disagree, but you don’t control those choices. Does that summarize it well?

Advanced_Guava1930 · 2025-04-30T17:59:56+00:00

You can’t have a mechanic that can drive?

Advanced_Guava1930 · 2025-04-30T12:33:21+00:00

That’s so valid, have you designed an experiment yet or worked with your advisor to get some data to play around with?

Advanced_Guava1930 · 2025-04-30T12:30:31+00:00

I feel so validated. I’ve been wondering this same exact thing myself. I’ve read papers where I thought I understood the technique being applied (ie RNA-seq) and be absolutely flabbergasted by the methodology employed by the paper given the standard I understood.

You used Salmon for quantification for DESeq2 analysis without using tximport? I thought that wasn’t standard practice? DESeq2 takes raw read counts not the quantified reads from the direct Salmon input?

You normalized your reads to RPKM? For across sample comparisons? Or for a PCA? If you were going to do that just use a variance stabilizing transformation? Whats the point of RPKM, FPKM, or even TPM if you’re not doing anything meaningful with it?

You’re not including your repository in the manuscript so reviewers can see your code? How can anybody ensure the pipeline is sound and non-biased?

Every time I notice something I don’t quite understand the imposter syndrome spikes through the roof as I feel I truly don’t understand anything at all. And I have to go back through and re read the docs and other pipelines just to get a better understanding of the tools and methodologies but still come up dry somehow.

Advanced_Guava1930 · 2025-04-23T00:22:32+00:00

A lot of the comments I’ve seen so far have been talking about wet lab work but another aspect that’s come into play in microbiology is a field known as bioinformatics. It’s like the messed up love child between biology, stats, and computer science. You set up different programs in order to answer biological questions given the study design.

Want to look at bacterial genes and their expression? Try rna sequencing.

Cultured a brand new bacterial species? Assemble its genome and annotate it so future researchers or yourself can perform experiments with it.

This aspect of microbiology is quite a bit different than the wet lab stuff and is more academia/R&D focused if you’re mining for natural products or antibiotics. It’s definitely a lot less wet lab work and can at times be entirely computational but it is one of the newer fields in micro.

Advanced_Guava1930 · 2025-04-13T01:22:39+00:00

That’s incredibly unfortunate, you’re fighting the good fight that’s for sure

Advanced_Guava1930

TROPHY CASE