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BCR tutorial #542

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f07d847
Added beta-version v2 of bcr tutorial and adapted corresponding file …
MKanetscheider Aug 22, 2024
9de8b8d
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Aug 22, 2024
d769b36
Fixed issues with citation, leading to a fail of build-the-docs
MKanetscheider Aug 22, 2024
28feb21
Added missing citations and removed references to in-work functions
MKanetscheider Aug 22, 2024
fa2171a
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Aug 22, 2024
f64e336
Fixed an issue with one citation
MKanetscheider Aug 22, 2024
b8c5358
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Aug 22, 2024
56b3ba5
Updated glossary to match new BCR functionalities and offer the user …
MKanetscheider Aug 26, 2024
d2ee583
Reference to new glossary entries
MKanetscheider Aug 26, 2024
d44c59c
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Aug 26, 2024
2684a58
Fixed faulty citation
MKanetscheider Aug 26, 2024
3424006
Update tutorial
grst Oct 11, 2024
c2b8632
Merge branch 'main' into BCR_tutorial
grst Oct 11, 2024
19e6a8a
update tutorial
grst Oct 11, 2024
e0e7ea1
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Oct 11, 2024
1ef6712
Update notebook
grst Oct 11, 2024
422d99d
Update tutorial
grst Oct 11, 2024
287d97d
Merge branch 'main' into BCR_tutorial
MKanetscheider Oct 15, 2024
46c0e8f
Discussion regarding bimodality of dataset
MKanetscheider Oct 15, 2024
cb662b2
Remove sections that will be added in separate PR
grst Oct 17, 2024
be5d6cc
Merge branch 'main' into BCR_tutorial
grst Nov 1, 2024
1426be6
Improve wording
grst Nov 1, 2024
6bec158
Update CHANGELOG
grst Nov 1, 2024
d0c7e39
Add BCR tutorial to CI
grst Nov 1, 2024
94e414b
Fix glossary link
grst Nov 1, 2024
cad5768
Glossary updates
grst Nov 1, 2024
fe4911a
Update references to preprocessing tools
grst Nov 1, 2024
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Fix function reference
grst Nov 1, 2024
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1 change: 1 addition & 0 deletions .github/workflows/test-tutorials.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@ jobs:
tutorial:
- tutorial_3k_tcr.ipynb
- tutorial_io.ipynb
- tutorial_5k_bcr.ipynb
os:
- ubuntu-latest
python:
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6 changes: 6 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -8,6 +8,12 @@ and this project adheres to [Semantic Versioning][].
[keep a changelog]: https://keepachangelog.com/en/1.0.0/
[semantic versioning]: https://semver.org/spec/v2.0.0.html

## [Unreleased]

### Documentation

- Add a tutorial for BCR analysis with Scirpy ([#542](https://github.com/scverse/scirpy/pull/542)).

## v0.19.0

### Additions
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34 changes: 30 additions & 4 deletions docs/glossary.rst
Original file line number Diff line number Diff line change
Expand Up @@ -49,6 +49,16 @@ Glossary
:term:`CDR3<CDR>` nucleotide sequences, but might recognize the same antigen
because they have the same or similar CDR3 amino acid sequence.

This is especially relevant for BCR, because clonally related cell are likely to differ due to
:term:`somatic hypermutation <SHM>`. It is important to understand that there is currently no best practice or
go-to approach on how to define clonotype cluster for BCR, as it remains an active research
field (:cite:`Yaari.2015`). There exist many different approaches such as maximum-likelihood (:cite:`Ralph.2016`),
hierarchical clustering (:cite:`Gupta.2017`), spectral clustering (:cite:`Nouri.2018`), natural language
processing (:cite:`Lindenbaum.2021`) and network based approaches (:cite:`BashfordRogers.2013`). A recent
comparison study indicates that computationally more sophisticated clonal inference approaches do not
outperform simplistic, computational cheaper ones (:cite:`Balashova.2024`). That said, there is still a
need for more in-depth comparison studies to confirm these results.

See also: :func:`scirpy.tl.define_clonotype_clusters`.

Private clonotype
Expand Down Expand Up @@ -190,7 +200,7 @@ Glossary
Immune receptor.

BCR
B-cell receptor. A BCR consiste of two Immunoglobulin (IG) heavy chains and
B-cell receptor. A BCR consists of two Immunoglobulin (IG) heavy chains and
two IG light chains. The two light chains contain a variable region, which is
responsible for antigen recognition.

Expand All @@ -201,12 +211,24 @@ Glossary
under the `CC BY-4.0 <https://creativecommons.org/licenses/by/4.0/deed.en>`__ license,
obtained from `wikimedia commons <https://commons.wikimedia.org/w/index.php?curid=49935883>`__

SHM
Common abbreviation for "Somatic hypermutation". This process is unique to BCR and occurs as part
of affinity maturation upon antigen encounter. This process further increases the diversity of the
variable domain of the BCR and selects for cells with higher affinity. SHM introduces around one point mutation per 1000
base pairs (:cite:`Kleinstein.2003`) and is able to introduce (although rare) deletions and/or insertions (:cite:`Wilson.1998`).
Furthermore, SHM is not a stochastic process, but biased in multiple ways (e.g. intrinsic hot-spot motifs (reviewed in :cite:`Schramm.2018`))

Dual IR
:term:`IRs<IR>` with more than one pair of :term:`VJ<V(D)J>` and
:term:`VDJ<V(D)J>` sequences. While this was
previously thought to be impossible due to the mechanism of allelic exclusion
(:cite:`Brady2010-gh`), there is an increasing amound of evidence for a *bona fide*
dual-IR population (:cite:`Schuldt2019`, :cite:`Ji2010-bn`, :cite:`Vettermann2010`).
(:cite:`Brady2010-gh`), there is an increasing amount of evidence for a *bona fide*
dual-IR population (:cite:`Schuldt2019`, :cite:`Shi.2019`, :cite:`RobertaPelanda.2014`,
:cite:`Ji2010-bn`, :cite:`Vettermann2010`).

Recent evidence suggest that also B cells with three or more productively rearranged
H and/or L chains exist (:cite:`Zhu.2023`), which indicates how much of B cell development
is still unclear.

For more information on how *Scirpy* handles dual IRs, see the
page about our :ref:`IR model<receptor-model>`.
Expand Down Expand Up @@ -239,8 +261,12 @@ Glossary
Alellically included B-cells
A B cell with two pairs of :term:`IG` chains. See :term:`Dual IR`.

Isotypically included B-cells
Similar to :term:`Alellically included B-cells`, but expresses both IGL and
IGK and thus rearrangements are not on alleles of the same gene (= isotypic inclusion).

Clonotype modularity
The clonotype modularity measures how densly connected the transcriptomics
The clonotype modularity measures how densely connected the transcriptomics
neighborhood graph underlying the cells in a clonotype is. Clonotypes with
a high modularity consist of cells that are transcriptionally more similar
than that of a clonotype with a low modularity.
Expand Down
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