# Confusion on "no IR" definition in scirpy

**URL:** <https://discourse.scverse.org/t/confusion-on-no-ir-definition-in-scirpy/3989>\
**Category:** scirpy\
**Created:** [May 18, 2026, 8:15am UTC](https://discourse.scverse.org/t/confusion-on-no-ir-definition-in-scirpy/3989 "2026-05-18T08:15:33Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![osmanmerdan](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/osmanmerdan/32/1097_2.png) [@osmanmerdan](https://discourse.scverse.org/u/osmanmerdan)\
**Post date:** [May 18, 2026, 8:15am UTC](https://discourse.scverse.org/t/confusion-on-no-ir-definition-in-scirpy/3989/1 "2026-05-18T08:15:33Z")

</div>

Hi everyone,

In our lab, we use the BD Rhapsody scRNA seq pipeline. Results from our recent CD8+ T cells TCR sequencing analysis confused me regarding the no-IR definition.

Here is step-by-step code and sample output

```auto
# Load IR and GEX data
mudata.set_options(pull_on_update=False)
lib1 = mudata.read_h5mu('Bd_out.cellismo')['rna']
lib1_airr = ir.io.read_airr(path = 'Bd_out_VDJ_Dominant_Contigs_AIRR.tsv')
lib1_mu = mu.MuData({'rna': lib1, 'airr': lib1_airr})

# Collect TCR QC metrics from AIRR data
ir.pp.index_chains(lib1_mu)
ir.tl.chain_qc(lib1_mu)

```

Looking at the QC metric plots, I noticed an unusually high number of non-IR-tagged cells. I loaded the dominant contigs file and checked the entries for some of the cells tagged as no-IR. Code and output below:

```auto
>> lib1_mu.obs.loc['397582']

## Output---------------------
airr:receptor_type no IR
airr:receptor_subtype no IR
airr:chain_pairing no IR
Name: 397582, dtype: object
-------------------------------

>> ir.get.airr(lib1_mu[lib1_mu.obs['airr:chain_pairing'] == 'no IR', :], 
            chain='VJ_1', 
            airr_variable=['junction_aa', 'v_call', 'productive']).loc['397582']

## Output---------------------
VJ_1_junction_aa <NA>
VJ_1_v_call <NA>
VJ_1_productive <NA>
Name: 397582, dtype: object
-------------------------------

>> df = pd.read_csv('Bd_out_VDJ_Dominant_Contigs_AIRR.tsv', sep='\t')
>> df.loc[df['cell_id'] == 397582, 
       [
           'cell_id', 'cell_type_experimental', 
           'high_quality_cell_tcr_bcr', 'umi_count',
           'locus', 'sequence_id', 'productive', 'junction_aa',
           'v_call', 'd_call', 'j_call'
       ]
   ]

## Output---------------------

```

| cell\_id | cell\_type\_experimental | high\_quality\_cell\_tcr\_bcr | umi\_count | locus | sequence\_id | productive | junction\_aa | v\_call | d\_call | j\_call |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 397582 | T | False | 1 | TRA | 397582\_TRA\_1 | False | RAMSLITTCSTS | TRAV6D-3\*03 | NaN | TRAJ21\*01 |
| 397582 | T | False | 4 | TRB | 397582\_TRB\_1 | False | HLQCR\*TGAYEQYF | TRBV1\*01 | TRBD2\*01 | TRBJ2-7\*01 |
| 397582 | T | False | 2 | TRG | 397582\_TRG\_1 | False | CASW\*YSSGFHKVF | TRGV7\*02 | NaN | TRGJ1\*01 |
| | | | | | | | | | | |

```auto
>> from scirpy.util import DataHandler
>> params = DataHandler(data=lib1_mu, 
                     airr_mod='airr', 
                     airr_key='airr', 
                     chain_idx_key='chain_indices')
>> ir.get._has_ir(params)
ir_dat = ir.get.airr(lib1_mu, 
                     chain=['VJ_1', 'VDJ_1', 'VJ_2', 'VDJ_2'],
                     airr_variable=['junction_aa', 'v_call', 'd_call', 'j_call', 'productive'])
ir_dat['_has_ir'] = ir.get._has_ir(params)
ir_dat.loc['397582']

# Output -----------------
VJ_1_junction_aa <NA>
VJ_1_v_call <NA>
VJ_1_d_call <NA>
VJ_1_j_call <NA>
VJ_1_productive <NA>
VDJ_1_junction_aa <NA>
VDJ_1_v_call <NA>
VDJ_1_d_call <NA>
VDJ_1_j_call <NA>
VDJ_1_productive <NA>
VJ_2_junction_aa <NA>
VJ_2_v_call <NA>
VJ_2_d_call <NA>
VJ_2_j_call <NA>
VJ_2_productive <NA>
VDJ_2_junction_aa <NA>
VDJ_2_v_call <NA>
VDJ_2_d_call <NA>
VDJ_2_j_call <NA>
VDJ_2_productive <NA>
_has_ir False
Name: 397582, dtype: object
---------------------------

```

```auto
# Package version info:
anndata 0.12.14
awkward 2.8.10
matplotlib 3.10.8
mudata 0.3.8
muon 0.1.7
numpy 2.3.5
pandas 2.3.3
scanpy 1.12.1
scirpy 0.24.0
seaborn 0.13.2

```

So even though there are entries in the dominant contigs file, why do I get “no IR”? I don’t understand. Is it expected for some reason, or am I doing something wrong?

I can happily provide further info.

Thank you for your help.

Kind regards.

---

<div class="post-metadata">

**Author:** ![grst](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/grst/32/17_2.png) [@grst](https://discourse.scverse.org/u/grst)\
**Post date:** [May 25, 2026, 6:22pm UTC](https://discourse.scverse.org/t/confusion-on-no-ir-definition-in-scirpy/3989/2 "2026-05-25T18:22:45Z")

</div>

Hi @osmanmerdan,

thanks for your question. I think for the example you are showing the reason is that the chains are marked as non-productive. By default, `index_chains` does not consider non-productive chains. See also the `filter` parameter in the [index\_chains docs](https://scirpy.scverse.org/en/latest/generated/scirpy.pp.index_chains.html#scirpy-pp-index-chains).

Best,  
Gregor

---

<div class="post-metadata">

**Author:** ![osmanmerdan](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/osmanmerdan/32/1097_2.png) [@osmanmerdan](https://discourse.scverse.org/u/osmanmerdan)\
**Post date:** [May 26, 2026, 6:11pm UTC](https://discourse.scverse.org/t/confusion-on-no-ir-definition-in-scirpy/3989/3 "2026-05-26T18:11:57Z")

</div>

Thank you, now I see! I checked the documentation.

Best

Osman