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Record W2020540944 · doi:10.1002/humu.21259

Assessment of complement C4 gene copy number using the paralog ratio test

2010· article· en· W2020540944 on OpenAlexaff
Michelle M. A. Fernando, Lora Boteva, David Morris, Bi Zhou, Yee Ling Wu, Marja‐Liisa Lokki, C. Yung Yu, John D. Rioux, Edward J. Hollox, Timothy J. Vyse

Bibliographic record

VenueHuman Mutation · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesVersus ArthritisWellcome Trust
KeywordsLibrary scienceMedicineHistoryFamily medicineGerontology

Abstract

fetched live from OpenAlex

The complement C4 locus is in the class III region of the MHC, and exhibits copy number variation. Complement C4 null alleles have shown association with a number of diseases including systemic lupus erythematosus (SLE). However, most studies to date have used protein immunophenotyping and not direct interrogation of the genome to determine C4 null allele status. Moreover, a lack of accurate C4 gene copy number (GCN) estimation and tight linkage disequilibrium across the disease-associated MHC haplotypes has confounded attempts to establish whether or not these associations are causal. We have therefore developed a high throughput paralog ratio test (PRT) in association with two restriction enzyme digest variant ratio tests (REDVRs) to determine total C4 GCN, C4A GCN, and C4B GCN. In the densely genotyped CEU cohort we show that this method is accurate and reproducible when compared to gold standard Southern blot copy number estimation with a discrepancy rate of 9%. We find a broad range of C4 GCNs in the CEU and the 1958 British Birth Cohort populations under study. In addition, SNP-C4 CNV analyses show only moderate levels of correlation and therefore do not support the use of SNP genotypes as proxies for complement C4 GCN.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score1.000

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)0.0010.000

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 head0.024
GPT teacher head0.330
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2010
Admission routes1
Has abstractyes

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