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Record W3004894219 · doi:10.1016/j.isci.2020.100883

Genotyping and Copy Number Analysis of Immunoglobin Heavy Chain Variable Genes Using Long Reads

2020· article· en· W3004894219 on OpenAlex
Michael Ford, Ehsan Haghshenas, Corey T. Watson, S. Cenk Şahinalp

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueiScience · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsSimon Fraser University
FundersNational Institute of General Medical SciencesUniversity of LouisvilleNational Science FoundationIndiana UniversityNational Institutes of HealthSimon Fraser University
KeywordsIGHV@GenotypingCopy-number variationBiologyComputational biologyGeneticsImmunoglobulin heavy chainGenomeLocus (genetics)GeneGenotype

Abstract

fetched live from OpenAlex

One of the remaining challenges to describing an individual's genetic variation lies in the highly heterogeneous and complex genomic regions that impede the use of classical reference-guided mapping and assembly approaches. Once such region is the Immunoglobulin heavy chain locus (IGH), which is critical for the development of antibodies and the adaptive immune system. We describe ImmunoTyper, the first PacBio-based genotyping and copy number calling tool specifically designed for IGH V genes (IGHV). We demonstrate that ImmunoTyper's multi-stage clustering and combinatorial optimization approach represents the most comprehensive IGHV genotyping approach published to date, through validation using gold-standard IGH reference sequence. This preliminary work establishes the feasibility of fine-grained genotype and copy number analysis using error-prone long reads in complex multi-gene loci and opens the door for in-depth investigation into IGHV heterogeneity using accessible and increasingly common whole-genome sequence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.264
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it