Finally, we would like to thank @HumanPangenome
for making the #HPRC resources available, which helped us a lot in testing and perfecting our VRPG. And of course, our own ScRAP #yeast pangenome collection reported at evomicslab.org/db/ScRAPdb/ and www.nature.com/articles/s41...

Many thanks to our talented student Zepu Miao for leading the development of VRPG. Built upon VRPG, we are currently working on new development and discoveries with #pangenome graphs. Stay tuned!

To further demonstrate its functionality & scalability, we applied VRPG to the cutting-edge yeast and human reference pangenome graphs via a dedicated web portal at evomicslab.org/app/vrpg/

Especially, VRPG enables side-by-side visualization between the graph-based pangenome representation and the conventional primary-linear-reference-genome-based feature annotations, which greatly increases the Interpretability of pangenome graphs.

VRPG provides efficient & intuitive supports for exploring and annotating pangenome graphs along a linear-genome-based coordinate system and offers many highly useful features such as in-graph path highlighting, CNV and SV characterization, graph-based sequence query, etc.

To facilitate better exploration & understanding of pangenome graphs towards novel biological insights, here we present a web-based interactive Visualization and interpretation framework for linear-Reference-projected Pangenome Graphs (VRPG).

In the era of #T2T genomics, #pangenome graphs have emerged as a new paradigm for identifying, encoding, and presenting genomic variation at population levels. However, it remains challenging to dissect and interpret pangenome graphs in a biologically informative manner.

The code of NanoTrans can be freely accesible via @github
at github.com/yjx1217/Nano...

As real case demonstrations, we applied NanoTrans to the public DRS datasets of yeast, Arabidopsis, as well as human embryonic kidney and cancer cell lines to showcase its utility, effectiveness, and efficacy across diverse systems and application settings.

Starting from the raw sequencing reads, NanoTrans can perform read basecalling, isoform clustering & quantification, differential gene expression & splicing, RNA modification, poly(A) tail length profiling, and fusion gene detection in a highly streamlined fashion.