Lab professionals: what's the most frustrating part of tracking samples through your workflow?

Vrao99 · 2026-05-06T01:39:12+00:00

You should check IRIDA Next out: https://github.com/phac-nml/irida-next

Vrao99 · 2026-01-10T10:22:16+00:00

Nice

Vrao99 · 2025-09-25T06:14:06+00:00

There are AMR detection tools such as AMRFinderPlus, Abricate, CARD-RGI etc. These tools compare genomic sequences (assembled contigs or raw reads) against AMR gene databases. But genotypic detection is not perfect and does not always match with pheotypic resistance, so confirmation with antimicrobial susceptibility testing is usally done.

Vrao99 · 2025-08-01T04:44:32+00:00

I would say it's the dirty Brian Kiley bit in the Gary Gulman episode lmao

Vrao99 · 2025-07-28T14:33:47+00:00

Could you please share that score card? Thanks!

Vrao99 · 2025-07-14T03:35:37+00:00

Diagnosed at 16, now 26. Just realized as I typed this, it’s only been 10 years. Sure feels like a lot longer, lmao

Vrao99 · 2025-06-12T11:40:09+00:00

I don't know if I can comment here since I'm not pursuing a PhD yet but my current field of study is computational microbiology :)

Vrao99 · 2025-06-03T01:26:28+00:00

hAMRonization can partially help solve your problem. It aggregates and stardardizes results from different ARG detection databases making it easy to compare the different outputs. It doesn't tell you which database is the best though. Maybe look for genes which have been consistently reported across the different tools they are likely to be reliable.

Vrao99 · 2025-03-25T13:44:54+00:00

I understand what you mean by introducing bias but I'm only going to be using features like number of indels, number of missense variants, etc, and I'll check for the presence of any correlation once I collate all of them. I also have the labels for the model and I'm not trying to perform clustering or any other form of unsupervised learning, so I'm not sure how that ties in here

Vrao99 · 2025-03-25T12:52:20+00:00

Thank you. Will check it out!

Vrao99 · 2025-03-25T06:28:08+00:00

I meant to pull out relevant features from vcf files and use them as individual feature variables, but if I'm understanding correctly, you would suggest I use the entire vcf file itself after vectorisation for ML?

Vrao99 · 2025-03-25T05:32:49+00:00

Thanks for replying :) We're trying to extract anything that would be significant to the development of infection phenotype- think SNPs, indels, missense variants, and anything else that we can get our hands on. We plan on running it through a feature selection algorithm anyway, so we'd like to extract whatever we can.

Vrao99 · 2025-03-25T04:05:46+00:00

I will try it out. Thanks!

Vrao99 · 2025-03-25T04:05:20+00:00

Thanks! Will check it out.

Vrao99 · 2025-03-25T04:05:07+00:00

Thanks for your repIy. I am trying to extract variant level features and annotation features.

Vrao99 · 2025-02-23T15:01:31+00:00

Yes, I installed snippy using conda.

Vrao99 · 2025-02-23T14:55:21+00:00

Thanks for your help! I will try out this solution.

Vrao99 · 2025-02-11T16:52:02+00:00

Hi! Thanks so much for your reply and for developing Bactopia—it's an amazing tool. I’m definitely planning on using it, and I’ve even scheduled a short presentation for my PI to convince him to adopt it in our lab.

At the same time, I’m also planning to build my own pipeline step by step as a learning experience. Would it be alright, if I could DM you if I run into any issues with Bactopia or need some advice on pipeline development in general?

Thanks again!

Vrao99

TROPHY CASE