Product partition latent variable model for multiple change-point detection in multivariate data

<div><p>The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.</p></div

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Additional file 3: of polyClustR: defining communities of reconciled cancer subtypes with biological and prognostic significance

Figure S3. Comparison of community classifications from each reconciliation method with intrinsic breast cancer subtypes. (A-B) Heatmap showing hypergeometric test with overlap between the subtype communities (from polyClustR) and the known subtypes from A) hypergeometric and B) PMI reconciliation methods. Norm – normal-like subtype; LumA – luminal A subype; Lum B – luminal B subtype. (PDF 50 kb

Additional file 4: of polyClustR: defining communities of reconciled cancer subtypes with biological and prognostic significance

Figure S4. Silhouette width of each sample and community in breast cancer for each reconciliation method –hypergeometric (HYP; left) and PMI (right). Colors represent distinct subtype communities. (PDF 21 kb

Additional file 2: of polyClustR: defining communities of reconciled cancer subtypes with biological and prognostic significance

Figure S2. Gene Set Enrichment Analysis (GSEA) analysis between subtypes in breast cancer. (A-F) GSEA analysis between the A) bNMF2 and B) bNMF6 breast cancer clusters, showing gene enrichment of metaplastic breast cancer and 17q21–25 amplicon signatures and C-F) between the two basal-subtype (bKM1 and bKM4) k-means clusters, showing enrichment of invasive and immune-related gene sets in bKM4 cluster. (PDF 119 kb

Additional file 7: of polyClustR: defining communities of reconciled cancer subtypes with biological and prognostic significance

Figure S7. Silhouette width of each sample and community in uveal melanoma for each reconciliation method – hypergeometric (HYP; left) and PMI (right). Colors represent distinct subtype communities. (PDF 19 kb

Additional file 6: of polyClustR: defining communities of reconciled cancer subtypes with biological and prognostic significance

Figure S6. Comparison of community classifications from each reconciliation method with known chromosome 3 ploidy statuses in uveal melanoma. (A-B) Heatmap showing hypergeometric test with overlap between the subtype communities (from polyClustR) and the known ploidy status from A) hypergeometric and B) PMI reconciliation methods. (PDF 53 kb