Advancing the Counseling Profession Through Contemporary Quantitative Approaches

Andrew W. Wood; Stephanie Dorais; Daniel Gutierrez; C. Missy Moore; Michael K. Schmit

doi:10.1002/jcad.12363

Advancing the Counseling Profession Through Contemporary Quantitative Approaches

Journal of Counseling & Development ◽

10.1002/jcad.12363 ◽

2021 ◽

Vol 99 (2) ◽

pp. 156-166

Author(s):

Andrew W. Wood ◽

Stephanie Dorais ◽

Daniel Gutierrez ◽

C. Missy Moore ◽

Michael K. Schmit

Keyword(s):

Counseling Profession ◽

Quantitative Approaches

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Theoretical and Quantitative Approaches to the Study of Mortuary Practice

10.30861/9781841710051 ◽

1999 ◽

Cited By ~ 9

Author(s):

Feldore McHugh

Keyword(s):

Mortuary Practice ◽

Quantitative Approaches

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The Return of Quantitative Approaches to Canadian History

Canadian Historical Review ◽

10.3138/chr-2020-0022 ◽

2020 ◽

Vol 101 (4) ◽

pp. 585-601

Author(s):

Peter Baskerville ◽

Kris Inwood

Keyword(s):

Canadian History ◽

Quantitative Approaches

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Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

Nature Communications ◽

10.1038/s41467-021-23821-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Verónica Lloréns-Rico ◽

Sara Vieira-Silva ◽

Pedro J. Gonçalves ◽

Gwen Falony ◽

Jeroen Raes

Keyword(s):

Microbial Communities ◽

Quantitative Methods ◽

Microbial Load ◽

Metagenomic Sequencing ◽

Sampling Depth ◽

Microbiome Research ◽

Microbiome Data ◽

The Impact ◽

Analytical Approaches ◽

Quantitative Approaches

AbstractWhile metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

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