{"doi":"10.1101/2022.11.09.515787","title":"Ibex: Variational autoencoder for single-cell BCR sequencing","abstract":"Abstract Summary B cells are critical for adaptive immunity and are governed by the recognition of an antigen by the B cell receptor (BCR), a process that drives a coordinated series of signaling events and modulation of various transcriptional programs. Single-cell RNA sequencing with paired BCR profiling could offer insights into numerous physiological and pathological processes. However, unlike the plethora of single-cell RNA analysis pipelines, computational tools that utilize single-cell BCR sequences for further analyses are not yet well developed. Here we report Ibex, which vectorizes the amino acid sequence of the complementarity-determining region 3 (cdr3) of the immunoglobulin heavy and light chains, allowing for unbiased dimensional reduction of B cells using their BCR repertoire. Ibex is implemented as an R package with integration into both the Seurat and Single-Cell Experiment framework, enabling the incorporation of this new analytic tool into many single-cell sequencing analytic workflows and multimodal experiments. Availability and Implementation Ibex is available as an R package at https://github.com/ncborcherding/Ibex . Reproducible code and data for the figure appearing in the manuscript are available at https://github.com/ncborcherding/Ibex.manuscript . A companion TCR-based approach is available at https://github.com/ncborcherding/Trex .","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":300592,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9502,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":625343,"name":"Bo Sun","orcid":"0000-0002-5507-6657","position":1,"is_corresponding":false},{"id":103960,"name":"David G. DeNardo","orcid":"0000-0002-3655-5783","position":2,"is_corresponding":false},{"id":230315,"name":"Jonathan R. Brestoff","orcid":"0000-0002-7018-7400","position":3,"is_corresponding":false},{"id":251348,"name":"Nicholas Borcherding","orcid":"0000-0003-1427-6342","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":null,"created_at":"2026-07-19T00:31:53.559757Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}