Results of sample disease state prediction using SVM algorithm with DA taxa identified by DESeq2-phyloseq as features, before and after imputation by TphPMF.

A. PR-AUC for disease state classification prediction. B. Abundance distribution of three example taxa identified by DESeq2-phyloseq after TphPMF, which were not identified before imputation, in the dataset by Yu et al. [<a href="http://www.plos...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Xinyu Han (2237545) (author)
مؤلفون آخرون:	Kai Song (107003) (author)
منشور في:	2025
الموضوعات:	Biochemistry Microbiology Cell Biology Genetics Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified type 2 diabetes predicting disease conditions particularly showing advantages machine learning approach detecting differentially abundant microbiome datasets pertaining data sparsity represents microbiome data imputation tphpmf significantly improves sparse data microbiome research xlink "> tphpmf enhances thereby undermining termed tphpmf statistical analyses potential non formidable challenge biological zeros
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الوصف
الملخص:	<p><b>A.</b> PR-AUC for disease state classification prediction. <b>B.</b> Abundance distribution of three example taxa identified by DESeq2-phyloseq after TphPMF, which were not identified before imputation, in the dataset by Yu et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012858#pcbi.1012858.ref041" target="_blank">41</a>], where the upper three graphs represent the abundance distribution before imputation, and the lower three graphs represent the distribution after imputation. <b>C.</b> Abundance distribution of three example taxa identified by DESeq2-phyloseq after TphPMF, which were not identified before imputation, in the dataset by Zeller et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012858#pcbi.1012858.ref042" target="_blank">42</a>].</p>

Results of sample disease state prediction using SVM algorithm with DA taxa identified by DESeq2-phyloseq as features, before and after imputation by TphPMF.

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