Selected article for: "average distance and multidimensional scaling"
Author: Josset, Laurence; Zeng, Hui; Kelly, Sara M.; Tumpey, Terrence M.; Katze, Michael G.
Title: Transcriptomic Characterization of the Novel Avian-Origin Influenza A (H7N9) Virus: Specific Host Response and Responses Intermediate between Avian (H5N1 and H7N7) and Human (H3N2) Viruses and Implications for Treatment Options
  • Document date: 2014_2_4
    • ID: uz0m1o0q_28
    Snippet: Transcriptomic distance analysis. To visualize transcriptional similarity between samples in a 2-dimensional space, Euclidian distances were calculated with transcriptomic normalized data, and nonmetric multidimensional scaling (MDS) was performed using the MASS software package in the R Bioconductor program (44) to map the distances into the 2-dimensional space with minimal loss of information (evaluated by Kruskal's stress). Biological replicat.....
    Document: Transcriptomic distance analysis. To visualize transcriptional similarity between samples in a 2-dimensional space, Euclidian distances were calculated with transcriptomic normalized data, and nonmetric multidimensional scaling (MDS) was performed using the MASS software package in the R Bioconductor program (44) to map the distances into the 2-dimensional space with minimal loss of information (evaluated by Kruskal's stress). Biological replicates from the same condition were linked in convex hulls (i.e., polygons) using the function "chull" in R. Pearson correlation coefficients, Spearman correlation coefficients, total Euclidean distances, or total Manhattan distances were used to estimate similarities in the gene expression profiles between Anhui01-infected and other IAV-or mock-infected samples. The average distance between conditions was calculated as the arithmetic mean of distances between all biological replicates.

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