Unexpected chain pairing status while converting AirrCells to AnnData

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1

Hi,

I encounter an unexpected behavior while converting a AirrCells object to AnnData.

However, some cells seem to be lost when converting airr_cells_new to adata_new at the end.

# Convert to AnnData
adata_new = ir.io.from_airr_cells(airr_cells_new)
# Get updated chain_pairing status, with no filtering
ir.pp.index_chains(adata_new, filter=(lambda x: True, lambda x: True))
ir.tl.chain_qc(adata_new)

## Counting chains in AirrCell objects:
pd.DataFrame([len(cell.chains) for cell in airr_cells_new]).value_counts()

> 2    3433
> 1     146
> Name: count, dtype: int64

## Chain pairing status of the AnnData object:
adata_new.obs['chain_pairing'].value_counts()

> chain_pairing
> single pair    3432
> orphan VJ       133
> orphan VDJ       14
> Name: count, dtype: int64

Which means that there is one cell with 2 chains which is converted to either “orphan VJ” or “orphan VDJ” .

Am I missing something?

More context:

The AirrCells object is defined by hand. Here is the core run to define airr_cells_new.
The script’s purpose is to manually remove secondary chains from an AnnData object.

airr_cells = ir.io.to_airr_cells(adata)

# Initiate empty AirrCell object to populate
airr_cells_new = []

# Convert additional chains into new cells
for ind, cell in enumerate(airr_cells):
    if len(cell.chains) <= 2:
        new_cell = cell
    elif len(cell.chains) > 2:
        ## Check that there are at most 4 chains, in concordance with the dual IR model
        assert len(cell.chains) <= 4
        
        chain_indices = adata.obsm['chain_indices'][ind]
        new_cell = ir.io.AirrCell(cell_id=f'{cell.cell_id}_prim')
        
        ## Select primary VJ chain if it exists
        if chain_indices.tolist()['VJ'][0] is not None:
            prim_vj_chain = cell.chains[chain_indices.tolist()['VJ'][0]]
            ## Add it
            new_cell.add_chain(prim_vj_chain)
        
        ## Select primary VDJ chain if it exists
        if chain_indices.tolist()['VDJ'][0] is not None:
            prim_vdj_chain = cell.chains[chain_indices.tolist()['VDJ'][0]]
            ## Add it
            new_cell.add_chain(prim_vdj_chain)
        
    # Add new cell to list
    airr_cells_new.append(new_cell)
2

Yes, if there were two VJ or two VDJ chains, it would still be orphan. A “singe pair” is always VJ+VDJ. Does that make sense?

3

I agree, and the case of two VJ and VDJ chains can happen.
However, because of how airr_cells_new is computed, this is not the case for any cell:

for cell_new in airr_cells_new:
        assert set([chain['locus'] for chain in new_cell.chains]) == {"TRA", "TRB"}
4

Hi, sorry for the late reply.

Given that you filter with filter=(lambda x: True, lambda x: True) and

assert set([chain['locus'] for chain in new_cell.chains]) == {"TRA", "TRB"}

for all cells, I don’t immediately see why this would happen.

Can you share with me the AirrCell objects (e.g. using pickle.dump()) of the offending cells that I can investigate? Alternatively the h5ad file. If you can’t share the data publicly, you can PN me via discourse or find my email on my GitHub profile.

5

Hi,
In turn, sorry for my late reply.

This was actually due to a mistake from my part. In the above code, the line:

creates a cell with a different cell_id, while for len(cell.chains) <= 2 the new_cell object is defined with the same cell_id.

I removed this and it all works as it should. Thanks.

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