Molecular diagnosis of 22q11.2 deletion and duplication by multiplex ligation dependent probe amplification
Bibliographic record
Abstract
22q11 Deletion syndrome (22q11DS) is the most common microdeletion syndrome in humans, occurring with an incidence of 1 in 4,000. In most cases the submicroscopic deletion spans 3 Mb, but there are a number of other overlapping and non-overlapping deletions that generate a similar phenotype. The majority of the 22q11.2 microdeletions can be ascertained using a standard fluorescence in situ hybridization (FISH) assay probing for TUPLE1 or N25 on 22q11.2. However, this test fails to detect deletions that are either proximal or distal to the FISH probes, and does not provide any information about the length of the deletion. In order to increase the detection rate of 22q11.2 deletion and to better characterize the size and position of such deletions we undertook a study of 22q11.2 cases using multiplex ligation dependent probe amplification (MLPA). We used MLPA to estimate the size of the 22q11.2 deletions in 51 patients positive for TUPLE1 or N25 (FISH) testing, and to investigate 12 patients with clinical features suggestive of 22q11DS and negative FISH results. MLPA analysis confirmed a microdeletion in all 51 FISH-positive samples as well as microduplications in three samples. Further, it allowed us to delineate deletions not previously detected using standard clinical FISH probes in 2 of 12 subjects with clinical features suggestive of 22q11DS. We conclude that MLPA is a cost-effective and accurate diagnostic tool for 22q11DS with a higher sensitivity than FISH alone. Additional advantages of MLPA testing in our study included determination of deletion length and detection of 22q11.2 duplications. (c) 2007 Wiley-Liss, Inc.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".