A genotype resource for postmortem brain samples from the Autism Tissue Program
Bibliographic record
Abstract
The Autism Tissue Program (ATP), a science program of Autism Speaks, provides researchers with access to well-characterized postmortem brain tissues. Researchers access these tissues through a peer-reviewed, project-based approval process, and obtain related clinical information from a secure, online informatics portal. However, few of these samples have DNA banked from other sources (such as a blood sample from the same individual), hindering genotype-phenotype correlation and interpretation of gene expression data derived from the banked brain tissue. Here, we describe an initiative to extract DNA from Brodmann Area 19, and genotype these samples using both the Affymetrix Genome-Wide Human SNP Array 6.0 and the Illumina Human1M-Duo DNA Analysis BeadChip genome-wide microarray technologies. We additionally verify reported gender, and infer ethnic background from the single nucleotide polymorphism data. We have also used a rigorous, multiple algorithm approach to identify genomic copy number variation (CNV) from these array data. Following an initial proof of principle study using two samples, 52 experimental samples, consisting of 27 subjects with confirmed or suspected autism and related disorders, 5 subjects with cytogenetically visible duplications of 15q, 2 with epilepsy and 18 age-matched normal controls were processed, yielding high-quality genotype data in all cases. The genotype and CNV data are provided via the ATP informatics portal as a resource for the autism research community.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".