The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
OmicsBraid 0.2.2
Frozen manuscript release
- Frozen the covariance-aware v0.2.2 statistical core used for
manuscript analyses.
- Provides subject-level permutation calibration for the cross-omic
omnibus test.
- Provides null-shift matched-subject bootstrap calibration for
Q_omics.
- Retains analytic confidence intervals as default reporting and BCa
layer intervals as sensitivity analysis.
- Retains covariance-aware GLS trajectory inference and hierarchical
confirmatory/suggestive braid classification.
- Includes Evidence Forest, Effect Braid, braid heatmap, concordance
map, export helpers, and known-truth simulation.
- Adds public-facing GitHub/pkgdown/release documentation without
altering the frozen
R/ statistical source.
Development history
OmicsBraid 0.2.2
Robust empirical calibration
- Adds
empirical_omics_tests() for resampling-calibrated
cross-omic inference.
- Global omnibus evidence can be calibrated by matched-subject
group-label permutation or by centered matched-subject bootstrap.
- Cross-omic heterogeneity can be calibrated by a raw-data null-shift
matched-subject bootstrap (recommended) or an effect-level centered
bootstrap under the fitted common-effect null; naive label permutation
is deliberately not used for this composite null.
- The permutation omnibus uses a covariance-aware Mahalanobis/Wald
statistic calibrated by the joint subject-level permutation
distribution. Empirical heterogeneity uses a covariance-aware GLS
residual quadratic statistic calibrated by matched-subject bootstrap
nulls. Both avoid requiring a chi-square reference distribution under
heavy tails.
- Asymptotic p-values are preserved alongside empirical p-values.
run_omics_braid() reports empirical tests only when
explicitly requested; empirical p-values are not made primary unless
empirical_use_as_primary = TRUE.
- Layer CI workflow now also exposes the already-supported
basic bootstrap interval.
- Adds a final targeted robust-calibration benchmark comparing
asymptotic, permutation, centered-bootstrap, and null-shift-bootstrap
Type-I error, inversion power, and analytic/basic/percentile/BCa
interval coverage.
- Adds persistent internal-disk checkpointing for the final
robust-calibration run (
04_RUN_ROBUST_CALIBRATION.R).
- The validated v0.1.9/v0.2.1 braid classifier logic is otherwise
unchanged.
OmicsBraid 0.2.1
- I/O-resilience patch for confirmatory validation; statistical
algorithms and simulation design are unchanged from v0.2.0.
- Confirmatory checkpoints and high-frequency outputs are now written
to persistent internal-disk storage under
~/OmicsBraid_ValidationCache/confirmatory_v020_design.
- Valid checkpoints from an interrupted v0.2.0 run are imported
automatically; incomplete/corrupt RDS files are ignored.
- Checkpoints are validated before reuse and written atomically via
temporary-file + rename.
- Final validation outputs are synchronized back to the package
_CONFIRMATORY_VALIDATION_OUTPUT folder only after the local
run completes.
OmicsBraid 0.2.0
- Froze the v0.1.9 omnibus/GLS/Q/equivalence/trend/classification
definitions for confirmatory validation rather than continuing
classifier redesign.
- Added
bootstrap_effect_intervals() with
subject-bootstrap percentile, basic, and BCa confidence intervals for
layer-specific Hedges’ g effects.
- Added
bootstrap_consensus_intervals() with
percentile/basic bootstrap confidence intervals for GLS consensus
effects.
- Added end-to-end
ci_method and
integrated_ci_method options to
run_omics_braid() while deliberately retaining analytic SEs
and p-values as the inferential basis.
- Preserved analytic intervals alongside bootstrap intervals
(
conf_low_analytic, conf_high_analytic) so
interval-method sensitivity is auditable.
- Added a targeted confirmatory simulation runner with n/group =
20/40/80/160/320, normal versus heavy-tailed residuals, Monte-Carlo
calibration intervals, CI-method comparisons, trend-power curves,
equivalence-power curves, covariance-assumption comparators,
decisive-classification safety metrics, checkpoint/resume support, and
validation figures.
- Added a focused BCa validation subset because BCa requires
leave-one-subject-out acceleration and is substantially more
computationally expensive.
- Added unit tests ensuring robust intervals are ordered/finite and
that changing the displayed CI method does not change analytic p-values
or omnibus inference.
- Version 0.2.0 is the confirmatory-validation build motivated by the
completed v0.1.9 benchmark, which showed strong core calibration but
mild heavy-tail undercoverage for analytic layer CIs.
OmicsBraid 0.1.9
- Added
test_braid_trend(), a covariance-aware GLS
trajectory test with a prespecified practical slope margin.
- Replaced raw observed-slope attenuation/amplification rules with
inferential trajectory states.
- Added hierarchical braid status: confirmed subtype,
direction-confirmed broader concordance, no-evidence, unresolved, and
insufficient.
- Added
no_detectable_effect to distinguish failure to
reject the joint null from demonstrated practical equivalence
(null_equivalent).
- Buffering/emergence remain confirmatory only when the required
layers pass equivalence testing; a separate
suggestive_pattern reports effect geometry when precision
is insufficient.
- Expanded simulation validation with Monte-Carlo intervals, trend
operating characteristics, exact versus hierarchical-family accuracy,
null-compatible outcomes, independence-assumption comparators,
scenario-failure reporting, and stratification by sample
size/correlation/missingness/distribution.
OmicsBraid 0.1.0
- Initial research implementation.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.