---
# System prepended metadata

title: '2022-10-05: open2c + higlass + scverse meeting'
tags: [' meeting', ' open2c', scverse]

---

---
tags: scverse, open2c, meeting
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# 2022-10-05: open2c + higlass + scverse meeting 

*Attendees:*

* Nezar Abdennur (Open2C, HiGlass)
* Geoff Fudenberg (Open2C)
* Nils Gehlenborg (HiGlass, Gosling, Vitessce)
* Ilya Flyamer (Open2C)
* Peter Kerpedjiev (HiGlass)
* Fritz Lekschas (HiGlass)
* Trevor Manz (HiGlass)
* Isaac Virshup (scverse)
* Ignacio Ibarra (scverse)
* Danila Bredikhin (scverse)
* Sasha Galitsyna (Mirny lab, Open2C)

## Agenda

* 1-2min intros
* 2-5min general presentation of community scope and projects
  * scverse (Danila)
  * Open2C (Nezar)
  * HiGlass (TBD)
* Topic discussion; possible topics:
  * genomic ranges
  * genomic metadata
  * multiscale genome x observation data (multivec)
  * sparse array formats and file storage (anndata, cooler)
  * visualization
  * data access APIs
* Areas of collaboration/ follow up?


## Notes

### Intros

* Ignacio - Postdoc in Munich
* Nezar – New PI at UMass – 
* Ilya – postdoc in Basel – wet + dry working on hic
* Danila – phd at EMBL – multiomics in scverse
* Nils – PI in harvard – interested in data storage for this and spatial
* Sasha –  – Previously worked in scatac, now involved with open2c
* Fritz – head of viz at biotech startup – worked on higlass
* Peter – SE & amazon – Prev higlass dev
* Jeff – Assist prof USC – HiC Analysis, cooltools, bioframe – polymer analysis
* Trevor – Phd w/ Nils, interning with Fritz – interest in data formats, currently working on higlass

### Presentations

* scverse
    * goals: maintanance, community
    * common storage + analysis tools
    * big current projects
        * community
        * spatial
        * regulatory genomics
        * scaling of data
* open2c
    * pairtools: aggregating hic data
    * file format: cooler
    * cooltools is ananlysis toolkit
    * polychrom for md simulations
    * bioframe: replacement for bedtools in python
    * higlass: sibling project for viz
    * cooler:
        * annotated sparse matrices
        * w/ binned genomic coordinates
        * collection of cooler
        * hdf5 + zarr
    * Chunked algorithms, currently largely custom
* higlass
    * Multiscale viz of genomic data
    * Currently working on factoring
    * Aligning 2d genome with 1d, but making this view more configurable
    * Applications
        * Viz across omics (also gosling + vitessce)
        * linked views
        * gosling grammar for viewing
    * HiGlass Manages datatypes
    * Main interest: managing data and datatypes well


### Discussions

* Data formats
    * client side: https://github.com/manzt/coolr
    * higlass-python v2 https://github.com/manzt/hg
    * if higlass formats were in zarr, would you need the server?
        * A: Probably not
    * tileset creation on the time
* Machine learning formats
    * Geoff – https://www.nature.com/articles/s41592-020-0958-x
    * hic with deep learning
        * genome confirmation modelling
        * Currently bound by GPU mem
        * Large sequences
        * Isaac: 2-bit encoding?
* Multivec
    * https://paper.dropbox.com/doc/Multivec-Spec--BVlBnY0uhAfONcAGYPV_oiS4Ag-3IelZjzjXDo7mGy3SkGUF
    * Could we converge with anndata?
    * Observation x genome bin 
    * Features not in anndata
        * chunk by chrom
            * (D) Can use MuData for that?
        * genomic metadata
            * (D) Would be great to standardise!
    * Fritz, Peter, Nils?, Trevor (?)
* Genomic range (Danila, Geoff)
    * Danila use case: atac seq, ranged summarized experiment
    * BioFrame genomic view (different views on a genome)
    * Nezar: problem of genome being a set of non contiguous views
    * Binned representation (bed-like vs bedgraph-like)
    * Maybe talk to dask for out of core?


### Follow up

* Genomic range/interval representations:
    * Metadata (genome assembly, etc.)
    * Binned genomic ranges (begGraph) vs arbitrary intervals (bed)
    * Deep learning representations
    * Schemas for known tabular formats
* File Formats:
    * Anndata + multivec
    * Multiscale data
    * Zarr, Parquet, Kerchunk
* Vis systems:
    * Memory usage
    * hg
    * higlass tileset "protocol"
    * Single-cell and single-locus embeddings
    * Standardized tileset adaptors for multiscale

