iSODA: A Comprehensive Tool for Integrative Omics Data Analysis in Single- and Multi-Omics Experiments
Bibliographic record
Abstract
Thanks to the plummeting costs of continuously evolving omics analytical platforms, research centers collect multiomics data more routinely. They are, however, confronted with the lack of a versatile software solution to harmoniously analyze single-omics and interpret multiomics data. We have developed iSODA, a web-based application for the analysis of single- and multiomics data. The tool emphasizes intuitive interactive visualizations designed for user-driven data exploration. Researchers can access a variety of functions ranging from simple visualization like volcano plots and PCA to advanced functional analyses like enrichment analysis and lipid saturation analysis. For integrated multiomics, iSODA incorporates multi-omics factor analysis and similarity network fusion. The ability to adapt the data on-the-fly allows for tasks, such as the removal of outlier samples or failed features, imputation, or normalization. All results are presented through interactive plots, the modular design supports extensions, and tooltips and tutorials provide comprehensive guidance for users. iSODA is accessible under http://isoda.online/.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.024 |
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".