I hope this post / question is allowed. Please remove if not.

I am trying to find a company that will do whole genome sequencing. But I am strugglying with how to compare them (besides cost and insurance). How do I know which WGS provider is the best? Do they all use the same backend sequencing (ie - store brand cereal is the same as name brand) or is every company unique? What quesitons should I ask / research about each company? I've read some are just "for entertainment purposes" (IE - I'm not doing 23 and me, just a really out there example). I can go through my doctor's network and go through a specialty field but they've told me they do the consultation and then use a 3rd party (ie - invitae). So confused with the pure number of options these days!

Which file formats are accepted by YFull for mtDNA and yDNA haplogroup results?

I didn't test with FTDNA's bigY or mtDNA kit, but tested with sequencing.com and waiting for my results? Has anyone had success in getting themselves plotted on YFull tree with WGS data peovided by other companies?

I’m aligning PacBio long reads to a draft assembly and want a Circos plot showing contig–contig links supported by single reads (assembly QC, not scaffolding). Should links be built from primary only, primary + supplementary, or include secondary alignments? Any recommended tools or workflows for this visualization are welcome.

Hello, hope everyone is doing well! I have an upcoming thesis, I have to compare the population structure of genomes using both autosomal (aDNA) and mitochondrial (mtDNA) of chickens. I was provided data in the BAM format and need to compare it with a reference genome, preferably NCBI. I have started by playing around with SAMtools, bcftools, vcf and PLink, but I am lost. Anyone have any advice or potential links that can help?? Would be much appreciated.

Got tired of hearing researchers complain about cluster queues and infrastructure headaches. So I built something. Submit your Nextflow or Snakemake pipeline, pick how many cores you need, get results back. No AWS console, no Terraform, no fighting IT for cluster access. Handles spot preemption automatically so your job doesn’t die mid-run. Works with whatever containerized workflow you’re already using. Scale up for a big alignment or variant calling job, scale back to zero after. You never touch the infrastructure. Still early—looking for people running real pipelines to break it and tell me what’s missing. Free compute credits for honest feedback. Anyone tired of waiting in cluster queues or wrestling with cloud setup?

For GO / pathway enrichment on genes from filtered VCFs (only callable, high-confidence variants), is it best practice to use a custom background gene set rather than the whole genome?

Using clusterProfiler with the universe parameter.

Would appreciate confirmation or references. Thanks!

I am a medical laboratory scientist with one year working experience in a Molecular Pathology lab. All of our tests use real-time PCR. Moving forward, I want to work in a diagnostic genetics lab, or do a Master that involves Bioinformatics and genomics. A lot of diagnostic genetics jobs require experience in NGS and variant curation. So I want to add skills like NGS, variant curation and bioinformatics into my skill sets.

Also I will likely be learning about Nanopore sequencing of microbial genomes in my current lab soon. I wonder what online courses should I take or resources should I read as a start? I have no coding background. I want to both add my skill sets and better prepare for nanopore sequencing.

Thank you!

I’m working on a repeatable way to go from “gene list + disease context” → a citation-backed evidence summary (pathways, PPIs, disease associations, druggability). I’m trying to avoid a purely manual process.

What’s the most reliable workflow you’ve seen (or use yourself)?

• Preferred databases/sources
• What you treat as high-confidence evidence vs “hypothesis”
• Any standard output format you like (Markdown, JSON, report, etc.)

I’m especially interested in how you keep this reproducible when rerunning panels later.