bio-applied-data-harmonization

SKILLWorkflowCommunity
v0.0.0Pavel-KravchenkoUnknownAktualisiert vor 1 Mon.Quelle →

Harmonize multi-omics data (RNA-seq, proteomics, methylation, metabolomics) before integration — per-layer normalization, KNN/half-minimum missing-value imputation, PCA/PVCA batch-effect detection, and ComBat correction with pandas/scikit-learn. Use when prepping matrices for MOFA2/DIABLO/mixOmics,

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vor 1 Mon.Letzte Aktualisierung
Skill
AutorPavel-Kravchenko
Version0.0.0
LizenzUnknown
KategorieWorkflow
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Harmonize multi-omics data (RNA-seq, proteomics, methylation, metabolomics) before integration — per-layer normalization, KNN/half-minimum missing-value imputation, PCA/PVCA batch-effect detection, and ComBat correction with pandas/scikit-learn. Use when prepping matrices for MOFA2/DIABLO/mixOmics, fixing missing values in proteomics MS data, or removing batch effects confounded with sequencing da

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