Summary: With the increased reliance on multi-omics data for bulk and single cell analyses, the availability of robust approaches to perform unsupervised learning for clustering, visualization, and feature selection is imperative. We introduce nipalsMCIA, an implementation of multiple co-inertia analysis (MCIA) for joint dimensionality reduction that solves the objective function using an extension to Non-linear Iterative Partial Least Squares (NIPALS). We applied nipalsMCIA to both bulk and single cell datasets and observed significant speed-up over other implementations for data with a large sample size and/or feature dimension.
View Article and Find Full Text PDFBackground: Pathologic tissue remodeling with scarring and tissue rigidity has been demonstrated in inflammatory, autoimmune, and allergic diseases. Eosinophilic esophagitis (EoE) is an allergic disease that is diagnosed and managed by repeated biopsy procurement, allowing an understanding of tissue fibroblast dysfunction. While EoE-associated tissue remodeling causes clinical dysphagia, food impactions, esophageal rigidity, and strictures, molecular mechanisms driving these complications remain under investigation.
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