# Interpreting scirpy's ir\_dist\_aa\_alignment distances

**URL:** <https://discourse.scverse.org/t/interpreting-scirpys-ir-dist-aa-alignment-distances/1697>\
**Category:** scirpy\
**Created:** [August 18, 2023, 6:55pm UTC](https://discourse.scverse.org/t/interpreting-scirpys-ir-dist-aa-alignment-distances/1697 "2023-08-18T18:55:04Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![drn11](https://avatars.discourse-cdn.com/v4/letter/d/9de053/32.png) [@drn11](https://discourse.scverse.org/u/drn11)\
**Post date:** [August 18, 2023, 6:55pm UTC](https://discourse.scverse.org/t/interpreting-scirpys-ir-dist-aa-alignment-distances/1697/1 "2023-08-18T18:55:04Z")

</div>

Hi,

I’m using `scirpy` for computing the distances between CDR3 AA sequences.  
For that I’ve called `pp.ir_dist` specifying `metric = 'alignment'`, `sequence = 'aa'`, and `cutoff = 15`.  
Trying to understand the behavior, I looked at an example entry in the CDR33 AA distance matrix that was created in my `mdata` object:

```auto
mdata["airr"].uns["ir_dist_aa_alignment"]["VDJ"]["distances"][6,8]
12.0

```

The corresponding CDR3 AA sequences are:

```auto
mdata["airr"].uns["ir_dist_aa_alignment"]["VDJ"]["seqs"][6]
'AARGTGGITAQLV'
mdata["airr"].uns["ir_dist_aa_alignment"]["VDJ"]["seqs"][8]
'AARTGGITAQLV'

```

If I run `R`’s `Biostrings::pairwiseAlignment`, using `BLOSUM62` as the substitution matrix, with `gapOpening = -11` and `gapExtension = -11` (consistent with `scirpy`’s `ir_dist_aa_alignment` parameters) I get:

```auto
Biostrings::pairwiseAlignment('AARGTGGITAQLV','AARGTGGITAQLV',substitutionMatrix="BLOSUM62",gapOpening=-11,gapExtension=-11)
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: AARGTGGITAQLV
subject: AARGTGGITAQLV
score: 62

Biostrings::pairwiseAlignment('AARTGGITAQLV','AARTGGITAQLV',substitutionMatrix="BLOSUM62",gapOpening=-11,gapExtension=-11)
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: AARTGGITAQLV
subject: AARTGGITAQLV
score: 56

Biostrings::pairwiseAlignment('AARGTGGITAQLV','AARTGGITAQLV',substitutionMatrix="BLOSUM62",gapOpening=-11,gapExtension=-11)
Global PairwiseAlignmentsSingleSubject (1 of 1)
pattern: AARGTGGITAQLV
subject: AAR-TGGITAQLV
score: 34

```

Following `scirpy`’s `AlignmentDistanceCalculator` function, the distance should be:  
min(62,56) - 34 = 22, and with the offset of 1, the entry in `mdata["airr"].uns["ir_dist_aa_alignment"]["VDJ"]["distances"][6,8]` should therefore be 23 (or actually 0 since 23 \> `cutoff = 15` I called the `pp.ir_dist` function with.

Can anyone help pointing me in the right direction?

---

<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:** [August 22, 2023, 6:28pm UTC](https://discourse.scverse.org/t/interpreting-scirpys-ir-dist-aa-alignment-distances/1697/2 "2023-08-22T18:28:17Z")

</div>

It seems the parasail implementation of the NW algorithm is inconsistent with the Biostrings package:

```python
>>> import parasail
>>> parasail.nw_trace_scan_16("AARGTGGITAQLV", "AARGTGGITAQLV", 11, 11, parasail.blosum62).score
62
>>> parasail.nw_trace_scan_16("AARTGGITAQLV", "AARTGGITAQLV", 11, 11, parasail.blosum62).score
56
>>> res = parasail.nw_trace_scan_16("AARGTGGITAQLV", "AARTGGITAQLV", 11, 11, parasail.blosum62)
>>> res.score 
45
>>> 56 - 45 + 1
12

```

Even though they arrive at the same alignment

```auto
>>> res.cigar.decode
'3=1I9='

```

which means 3 matches followed by 1 insertion followed by 9 matches which is exactly the same as in your example.

If you find out why they are different, please let me know!