Suitability and Advantages of Abundance-Weighted Algorithms for the Holistic Comparison of Sample Systems

Abstract

Numerous microcosmic research techniques have been available for examinations of individual chemicals (DNA, RNA, proteins, carbohydrates and other small-molecule chemicals) in sample systems. However, the results generated from many of the microcosmic studies have fueled speculations, hypotheses and non-conclusive debates in the study of systematics, similar to blind men each touching a portion of an elephant. To address this shortcoming, macrocosmic holistic techniques exhibit advantages in profiling and systematically comparing genetic diversity and genetic distance between sample systems, transcriptome and proteome expressions and metabolome/chemical constituent fingerprints. Although binary abundance-unweighted algorithms have been widely used in such holistic comparisons, most of the research data do not fall into an "all-or-none" qualitative category, leading to unsuitability of abundanceunweighted algorithms as analytic tools in these types of holistic comparisons. Using an RAPD molecular polymorphism study as the example, this paper reviews the prerequisites and limitations of the binary abundance-unweighted algorithms in holistic comparisons and the advantage of using abundance-weighted algorithms, which are mathematically general and suitable for any holistic analyses. Keywords: IntroductionAlthough numerous microcosmic research techniques have been developed and widely used to examine individual chemicals (DNA, RNA, proteins, carbohydrates and other small-molecule chemicals) in sample systems, macrocosmic holistic techniques exhibit advantages in systematic comparisons of genetic diversity and genetic distance between sample systems, transcriptome and proteome expressions and metabolome/chemical constituent fingerprints. In holistic research projects, binary abundanceunweighted algorithms have been widely used and are limited to two sample comparisons. However, most of data generated from holistic studies do not fall into an "all-or-none" qualitative research category; thus, abundance-unweighted algorithms may not serve as suitable analytic tools for these types of research. Using an RAPD molecular polymorphism study as the example, this paper reviews the prerequisites and limitations of using the binary abundance-unweighted algorithms and the advantage of abundance-weighted algorithms in holistic studies.Since 1999, PCR-based nrDNA Internal Transcribed Spacer (ITS) sequencing has been used to determine the taxonomic status of the examined fungal specimens in the natural Cordyceps sinensis insect-fungi complex as an auxiliary molecular method to examine the anamorph-teleomorph connection of Ophiocordyceps sinensis [1][2][3][4]. Scientists have reported the molecular heterogeneity of C. sinensis-associated fungi of the genera Hirsutella, Paecilomyces and Tolypocladium as well as Geomyces pannorum, Cladosporium macrocarpum, Phaeosphaeria pontiformis and Neosetophoma samarorum (in total, more than 90 species spanning at least 37 genera) [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]...