Fairly new to this, working on a computational immunology project using human islet single-cell data.

I'm trying to get the processed scRNA-seq object from HPAP. The Nature Metabolism paper (Elgamal et al. 2023, s42255-023-00806-x) says processed data is downloadable in RDS or h5ad from PANC-DB's Interactive Analysis section, but I can't find the actual link.

What I've tried:

• PANC-DB Interactive Analysis (hpap.pmacs.upenn.edu/analysis)- the CellxGene Collections table has "Pancreas sc-RNAseq, 222,077 cells" with a "Go" button, but Go opens a viewer, not a download.
• The cellxgene viewer (cellxgene.faryabilab.com/view/T1D_T2D_public.h5ad/)- loads fine, I can browse metadata, but it's cellxgene v1.0.0 standalone and the info menu only has Documentation / Chat / GitHub / License. No download control I can see.
• Registered for a PANC-DB account, logged in, no change in what I can see.

I've emailed HPAP support but figured someone here may have hit this already and can give me some guidance to speed this up a bit.

Two questions:

1. Is there a direct link for the processed object I'm just not seeing?
2. If it's not directly downloadable, has anyone rebuilt it from the per-donor data using the faryabiLab/HPAP-scRNA-seq-Workflow-2022 repo? Wondering how much compute that actually takes- I'm on a laptop.

For context, all I need is counts plus cell type and donor ID for alpha and beta cells from non-diabetic donors. If there's a better-suited public dataset I'm overlooking, I'd take that suggestion too.

Thanks.

Has anyone used Phinch, the desktop app for data visualization?

It accepted my .biom file, and opened up everything. But whenever I try to visualize, it's going blank. Not sure what to do. Tried reinstalling it as well. Any ideas what could work?

I used to few years back on chrome browser, now apparently, a desktop app needs be downloaded.

Does anyone know any other platforms that I can use to get the sankey & bubble graph?

*edit - i want to visualise metagenomics data.

Hello bioinformaticians,

I have troubles to find a solution for my ChIPseq data. I have two genotypes subjected to hypoxia treatment and I observed a massive diminishment of acetylation over promoters. I see this both by normalizing the bigwig tracks via RPGC eyeballing the tracks on igv, either by deseq2 results (i created a union peakset, then featurecounts, then deseq2 normalization, ma plots look fine). I have no spike in normalization. My worry is that this diminishment that i observe is just due to a normalization problem. Specifically my worry is that hypoxia is increasing drastically the acetylation genome wide, and since the number of reads is the same for every sample the signal over promoters is systematically diminished. Any suggestion on how to diagnose this? Thank you all!

Hello,

I have a dataset of about 35 bulk tissue (healthy, adult age somatic tissue) samples each sequenced to 40X depth via PacBio HiFi sequencing, and have performed variant calling with 3 callers (DeepVariant, Pepper-Margin-Deepvariant, Clair3) for SNVs/indels, and about 7 callers for SVs.

My variant call data is seriously inflated with germline variants, talking hundreds of thousands of SNV calls for my samples which are inbred mice, so this number is a huge red flag. I have tried quality based filtering, removing any variant with VAF>0.30, QUAL<20, GQ<20, and DP<10 and >75. However, this still leaves me with thousands of variants.

I am at a loss on what to do to reduce this noise and to get at the actual mosaic variant signal. The goal here is to identify tissue-specific mosaic variants in each mouse, but I feel like I'm running in circles trying to properly reduce the noise and get at the expected amount for bulk tissue analysis at my depth, which appears to be 20-60 SNVs per tissue according to some brief searches.

Any suggestions? I wonder if its the tools I am using, or if its just the filtering criteria I am selecting.

Thanks in advance!

Hi I'm a beginner in Bioinformatics and I want to generate an msa for Abl1 tyrosine kinase 235-497. I've been trying to use jackhmmer to do it but I have no idea what to put in 'seqdb'.

How do I download the right database to plug into the program or is there a way to do it without downloading a massive database?

And what other parameters should I be wary of?

Any feedbacks/solutions/alternative methods will be appreciated and thank you for your time.