Whole exome and genome sequencing for Mendelian immune disorders: from molecular diagnostics to new disease variant and gene discovery
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.
Bibliographic record
Abstract
Whole exome and whole genome sequencing are next generation sequencing (NGS) applications that enable investigation of all coding variants (around 20 000) or all variants (around 4 million) in the human genome. They provide an extremely powerful tool for detecting variants with an established implication in Mendelian disorders as well as for discovering new disease variants and genes. The large number of variants generated requires elaborate databases, prediction models, and integrated workflows to identify which variants are more likely to contribute to disease. We discuss the whole exome and whole genome options, review the sequencing platforms and variant calling pipelines available for different variant types, and devote most of the review to how genetic variants can be annotated and prioritized to identify the ones likely contributing to disorder. The application focus will be Mendelian disorders; disorders caused by rare or common variants with a more complex genetic architecture will only be discussed briefly. For variant annotation and interpretation, we will concentrate on smaller variants (substitutions, insertions, and deletions), only briefly reviewing structural and copy number variation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it