Selected article for: "PCA principal component analysis and principal component analysis"
Author: Lara Urban; Andre Holzer; J Jotautas Baronas; Michael Hall; Philipp Braeuninger-Weimer; Michael J Scherm; Daniel J Kunz; Surangi N Perera; Daniel E Martin-Herranz; Edward T Tipper; Susannah J Salter; Maximilian R Stammnitz
Title: Freshwater monitoring by nanopore sequencing
  • Document date: 2020_2_7
    • ID: 77nsidzc_10
    Snippet: Hierarchical clustering additionally showed that two biological replicates collected at the same location and time point (April samples 9.1 and 9.2), grouped with high concordance; this indicates that spatiotemporal trends are discernible even within a highly localised context. Besides the dominant core microbiome, microbial profiles showed a marked arrangement of time dependence, with water samples from April grouping more distantly to those fro.....
    Document: Hierarchical clustering additionally showed that two biological replicates collected at the same location and time point (April samples 9.1 and 9.2), grouped with high concordance; this indicates that spatiotemporal trends are discernible even within a highly localised context. Besides the dominant core microbiome, microbial profiles showed a marked arrangement of time dependence, with water samples from April grouping more distantly to those from June and August (Figure 2c ). Principal component analysis (PCA) (Figure 3a ; Extended Data Figure 4 ) revealed that the strongest differential abundances along the chronological axis of variation (PC3) derived from the higher abundance of Carnobacteriaceae in April (Figure 3b ). This family is known for its occurrence in waters with low temperature 20 .

    Search related documents:
    Co phrase search for related documents
    • component analysis and core microbiome: 1
    • component analysis and Hierarchical cluster: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • component analysis and high abundance: 1
    • component analysis and low temperature: 1, 2
    • component analysis and PCA principal component analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • component analysis and principal component analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • core microbiome and differential abundance: 1
    • core microbiome and principal component analysis: 1
    • Hierarchical cluster and PCA principal component analysis: 1, 2, 3
    • Hierarchical cluster and principal component analysis: 1, 2, 3, 4, 5, 6, 7, 8
    • high abundance and PCA principal component analysis: 1
    • high abundance and principal component analysis: 1
    • low temperature and principal component analysis: 1, 2