Immune Repertoire#
Tutorials for the omicverse.airr module — a unified analysis framework for
adaptive immune receptor repertoire sequencing (AIRR-seq: TCR / BCR).
ov.airr spans four regimes. The single-cell side is a clean, AnnData-native
reimplementation of the core of scirpy: reading
10x V(D)J / AIRR output, chain QC, exact and distance-based clonotype
definition, clonal expansion, clonotype networks, and repertoire metrics
(diversity, overlap, V(D)J usage, spectratype). The bulk + B-cell side
wraps standalone R-parity backend packages behind a registered,
method=-dispatch API: bulk repertoire analytics (pyimmunarch), the
Immcantation core (pyalakazam), somatic hypermutation (pyshazam), B-cell
clonal clustering (pyscoper), immunoglobulin genotyping (pytigger), and
B-cell phylogenetics (pydowser). The TCR-specificity side adds the
TCRdist metric, GLIPH2 motif grouping (pygliph), GIANA / clusTCR clustering,
meta-clonotype discovery and antigen-database annotation (VDJdb / McPAS /
IEDB); and the TCR + transcriptome side reimplements the core of
CoNGA for joint single-cell analysis.
Install the bulk / B-cell / GLIPH2 backends with pip install omicverse[airr];
single-cell, TCRdist and CoNGA-style analysis run on numpy / pandas / anndata
with no extra package.
- Single-cell TCR + transcriptome — the immune-repertoire pipeline
- Bulk TCR immune-repertoire analysis with
ov.airr - B-cell receptor repertoire analysis with
ov.airr - Single-cell BCR + transcriptome — clonal expansion, isotypes and somatic hypermutation
- TCR specificity analysis — grouping receptors by their antigen
- Joint single-cell TCR + gene-expression analysis — a CoNGA-style workflow