Additional file 1 of The application of epiphenotyping approaches to DNA methylation array studies of the human placenta
Bibliographic record
Abstract
Additional file 1: Fig. S1. Sample map for EPIC array processing. Depiction of sample distribution across Illumina Infinium MethylationEPIC array chips, colored by randomization variables (sex, SSRI exposure status, COSMOSS stress score, replicate status, trimester, cell type). Chips are grouped by batch. Fig. S2. Heatmap of the strength of association between pairs of covariates. R2 values of linear models run on Covariate ~ Covariate demographic variables. “Ethn” denotes ethnicity, “P(African/Asian/European)” refer to the continuous PlaNET ancestry probabilities, “SD” refers to standard deviation, “wt” refers to weight, “GA” refers to gestational age at birth, “Cyto” refers to cytotrophoblast, and “nRBC” refers to nucleated red blood cells. Fig. S3. Relationship between processing time and cell type proportions. (A) Placental processing time in hours after delivery (Proc time) is plotted along the Y axis, with cohort plotted along the X axis. (b) Estimates of cell type proportions (Y axis) were plotted against placenta processing time (hours) from all cohorts. Significant Pearson correlations (Estimate ~ Cell Type) are indicated with p < 0.05 in the figure legend. (C) Samples from the V-SSRI cohort were excluded, to evaluate the impact of processing time on cell type proportions independent of the few samples in V-SSRI with unusually long processing times. Significant Pearson correlations are indicated with p < 0.05 if the figure legend. Fig. S4. Relationship between cell type proportions and sex, self-reported maternal ethnicity, and PlaNET ancestry. (A, C, E) All Cohorts, (B,D,F) Vancouver-collected cohorts only, QF2011 cohort excluded. Significance of comparisons are indicated when p < 0.05. Fig. S5. Relationship between cell type proportions and placental to fetal weight ratio and residual. (A) Fetal to placental weight ratio association with cell type proportions. Significant correlations are indicated with p < 0.05 in the legend. (B) Residual of fetal weight regressed on placental weight showed no significant association with any cell type proportion. Fig. S6. Distribution of all nominal p values for linear models run with adjustment for epiphenotype variables. “Base” refers to the base linear model of DNAme ~ Cohort + Sentrix Position + Sex + ε. Additional models refer to the base model plus the specified additive covariate. For example, GA (gestational age) refers to DNAme ~ Cohort + Sentrix Position + Sex + GA + ε. P values investigated are those associated with the term “Cohort”. RRPC indicates robust refined placental clock, Ancestry refers to adjustment for PlaNET ancestry continuous values, Cells refers to adjustment for continuous PlaNET cell composition estimates. Listing > 1 variable indicates additive adjustment for all indicated variables (such as adjustment for both ancestry and cell composition as indicated by the notation Ancestry_Cells). A horizontal dashed line indicates p = 0.05. The p values shown in this plot arise from linear models run on V-SSRI and V-NORM (n = 99) at all filtered autosomal CpGs. Table S1. Lambda values from linear models for differential DNAme by Cohort. Lambda was calculated in each case from all nominal p values associated with the Cohort term in each model. GA refers to gestational age, RRPC refers to the robust refined placental clock gestational age, Ancestry and Cell Types refer to the PlaNET epiphenotype variables for ancestry and cell composition, included as continuous additive covariates.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.883 | 0.197 |
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".