Autoencoder-based sequence embedding about scirpy

[b-schubert]

Re future directions:

• theoretically, in mvTCR you also have independent transcriptomic and TCR spaces, though we have not fully explored their structures yet.
• I am teaching a single-cell analysis course this winter semester with student projects where we are going to explore VDJ encodings and pre-trained TCR models in mvTCR, we could also explore the options of how to integrate HLA types (more than just as confounding)

[grst]

Hi @michael-swift,

this is super cool! For interoperability with scirpy, the preferred way would now be to make a separate package that operates on an AnnData object with the scirpy data structure. To get started, I recommend checking out our cookiecutter template.

I am happy to promote such a package via the scirpy documentation and the scverse ecosystem page.

Also happy to help with any questions regarding how to make such a package fully interoperable with scirpy.

[FFinotello]

Thanks, @grst for putting this together! It might be worth embedding also HLA type information (see also this recent publication).

[ncborcherding]

Agreed deepTCR from @sidhomj would be a good addition to the list.

[drEast]

Happy to help integrating mvTCR into scirpy / sc-verse. Would you prefer having external packages with interfaces to Scirpy, or integrating them directly into the main package? The latter will potentially cause quite some dependencies-issues between the different tools.

As you mentioned, we are also currently working on a TCR embedding that is guided by antigen specificity (in contrast to most AE-based methods) and, therefore, potentially better clusters TCRs by their target epitope. However, development is still ongoing.

[grst]

I had a chat with @drEast yesterday, summarizing the main points below:

• mvTCR integrates exactly one pair of alpha/beta chains per cell with gene expression data
• it does not take into account V/D genes or HLA types
• It works in principle to integrate BCR data as well, but it is not validated. It does not make sense to have BCR/TCR in the same model.
• After submitting their preprint, they will work with me on making it compatible with scirpy as external package.

For the future the model could be extended

• to become more flexible, to optionally account for secondary chains and/or V/D genes
• return the TCR-space independently of the gene expression space

[grst]

theoretically, in mvTCR you also have independent transcriptomic and TCR spaces, though we have not fully explored their structures yet.

As I understood @drEast yesterday, as it is currently implemented, it cannot be ran independently of the transcriptomic module and it's also not possible to directly access the TCR space. But maybe that's just a minor implementation detail.

[FFinotello]

Hello everyone, and thanks for this great exchange! :)

For the HLA types, it would be great to keep track somehow of their sequence similarity. We could also consider their level of expression, at least broadly assigned to HLA-A, HLA-B, and HLA-C genes, whereas allele-specific expression would be hard to derive from 10x data.
But @b-schubert you are definitely the expert here :)

[michael-swift]

hey folks, I was thinking along similar lines and used ablang to investigate whether these LLMs are any good for looking at BCRs. see the post here:
https://michael-swift.github.io/posts/
I'm happy to help pull something useful into scirpy, lmk

[michael-swift]

thanks for the info! I'll look into making a package