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aggregate_enrichment() for multi-omics Late Fusion
at the pathway level by aggregating multiple
enrichResult/gseaResult objectsmethod = "brown" in aggregate_omics()method = "weighted_mean" in
aggregate_omics() for signed statistics with layer-specific
weightsmnsea() and mnsea_gson() for
multi-layer network-based enrichmentprepare_multilayer_network(),
propagate_multilayer(), and
collapse_multilayer_scores() for the multi-layer
propagation pipelinemnseaResult to store multi-layer diffusion results,
collapsed scores, layer weights, and cached explanation tablesmnseaResultget_mnsea_contribution() and
extract_mnsea_subnetwork() for explanation-ready data
extractionclusterProfiler::mnseGO(), mnseKEGG(),
mnseMKEGG(), and mnseWP()aggregate_omics(), harmonize_ids() and
select_features_for_ora() to support Multi-omics Early
Integration
conflict_policy parameter (“keep_all”, “strict”,
“penalty”) to handle directional conflicts in signed statistics
(2026-06-23, Tue)ora(), gsea(),
and nsea() through a decoupled aggregation layeraggregate_enrichment(), are designed to be reused by
downstream packages for high-level multi-omics analysisget_omics_contribution() and
classify_omics_pattern() for Multi-omics contribution
tracingweight parameter to ora(),
ora_gson(), gsea(), and
gsea_gson()BiasedUrn packagensea() and nsea_gson() for
network-ranked GSEA based on Random Walk with Restart (RWR)mode = "signed" support in nsea() and
nsea_gson() for bidirectional network propagation using
signed statisticsprepare_network() for parsing and normalizing edge
lists or sparse matricesRcppEigen sparse
matrix multiplicationclusterProfiler::nseGO(), nseKEGG(),
nseMKEGG(), and nseWP()fgsea::prepareStats() to reduce result drift relative to
the long-used fgsea backend (2026-06-22, Mon)
* 1e6 scaling in
prepare_gsea_inputs() with fgsea-style total-weight
normalization and integer roundinggsea(method = "multilevel") against
fgsea::fgseaMultilevel() on the same ranked inputora_gson() before
multiple-testing correction (2026-06-22, Mon)
Count = 0 rows out of
p.adjust/qvalue so ORA results match
historical DOSE/clusterProfiler behaviorclusterProfiler::enricher(), enrichKEGG(), and
compareCluster() workflows (e.g. compound KEGG analyses,
#821 & #819 of ‘clusterProfiler’)bayes_enrich() for estimating posterior
probabilities of active explanatory terms from enrichResult
objectsbayes_summary() to return Bayesian enrichment
results ordered by posterior probabilityas.data.frame() rows, all x@result
rows, or explicit term IDsenrichResult object with
posterior, posterior odds, Bayesian rank, active flag, and covered-gene
columnsTERM2NAME() for GSON objects to
map gsid to term names properlyTERMID2EXTID() for GSON objects to
return gene vectors by requested term ordercharacter(0) for missing terms to keep
downstream behavior stableDescription.* columns in downstream
clusterProfiler::groupGO()gsea_gson() (2026-03-10, Tue)
geneList to ensure result object is
consistent with inputenrichplot::gseaplot showing
incorrect metric/color alignmentcalculate_qvalue() (2026-02-02,
Mon)
qvalue package gracefullyqvalue() failsora_gson() (2026-02-02, Mon)
phyper instead of summing dhyper for
better performance and precisionsetReadable() to support converting gene ID to
other types (not limited to SYMBOL) (2026-01-21, Wed)organism slot in compareClusterResult
(2026-01-20, Tue)gsea_gson() and ora_gson()
(2026-01-11, Sun)
NA or duplicate gene set IDs in result rownames
to prevent errorscalculate_qvalue() (2026-01-11,
Sun)
ora_gson() output columns (2026-01-11, Sun)gseaScores function (2025-12-07, Sun)
ora_gson and gsea_gson
(2025-12-05, Fri)
enricher_internal and
GSEA_internalDOSE to
enrichit (2025-12-05, Fri)
clusterProfiler familygsea function (2025-12-04, Thu)
ora function (2025-12-03, Wed)
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.
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