Use of Affymetrix Arrays in the Diagnosis of Gene Copy‐Number Variation
Bibliographic record
Abstract
Diagnosing constitutional pathogenic copy number variants (CNVs) requires detecting submicroscopic segmental chromosomal imbalances. The Affymetrix GeneChip mapping array was one of the initial microarray platforms used to measure duplication and deletion of genetic material in DNA samples. Unlike oligonucleotide microarrays from NimbleGen and Agilent, developed around the same time to infer copy number status for the DNA sequence covered by the probe, the Affymetrix GeneChip system used 25-mer oligonucleotide probes designed to interrogate SNPs. Thus, it was possible to use the Affymetrix 'SNP chips' to both identify SNPs and to identify copy number status. Affymetrix now offers the CytoScan microarray platforms, which are optimized for copy-number analyses, and provides accompanying software. They also offer several other microarray platforms suitable for copy-number analyses. Here we discuss the application of the CytoScan high-density (HD) platform for the detection of genomic imbalance. We provide an overview of the sequence of computational analyses involved in identifying pathogenic CNVs and highlight important parameters for consideration in assessing the pathogenicity of a detected CNV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".