Simulation results for differential abundance analysis under the log-normal, Poisson, and negative-binomial models, respectively.

Simulation results for differential abundance analysis under the log-normal, Poisson, and negative-binomial models, respectively.

<p>Error bars represent the 95% confidence intervals and the dashed vertical line indicates the target FDR level of 0.05.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Huijuan Zhou (5745020) (author)
مؤلفون آخرون:	Jun Chen (4238) (author), Xianyang Zhang (2592901) (author)
منشور في:	2025
الموضوعات:	Microbiology Genetics Ecology Inorganic Chemistry Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified uses variational inference reconstructing true abundances real microbiome datasets multiple posterior samples microbiome sequencing data microbial biomarker discovery excessive zeros arising differential abundance analysis bimodal abundance distribution assume unimodal abundance computationally efficient solution efficient imputation taxa via scalable expectation require log probabilistic framework method offers maximization algorithm insufficient sampling inherently sparse downstream analyses dirichlet priors broadly applicable biological absence analyzing high accurate imputation
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

The BMDD model.
حسب: Huijuan Zhou (5745020)
منشور في: (2025)

Performance of BMDD in differential abundance analysis of microbiome data.
حسب: Huijuan Zhou (5745020)
منشور في: (2025)

Execution time of the BMDD algorithm.
حسب: Huijuan Zhou (5745020)
منشور في: (2025)

Imputation performance comparison of BMDD with competing methods across 15 distance metrics between the estimated and true composition matrices under settings S2–S9.
حسب: Huijuan Zhou (5745020)
منشور في: (2025)

Model fit and imputation performance of BMDD.
حسب: Huijuan Zhou (5745020)
منشور في: (2025)

Analysis results of the overlap of DA taxa captured by six DA analysis methods in the original and TphPMF-imputed datasets for two T2D and four CRC datasets. The first column shows the number of overlapping DA taxa in the original and TphPMF-imputed datasets for two T2D datasets; the second column shows the number of overlapping DA taxa in the original and TphPMF-imputed datasets for four CRC datasets; the third column shows the proportion of overlapping taxa in the total DA taxa identified in the original and TphPMF-imputed datasets for two T2D datasets; the fourth column shows the proportion of overlapping taxa in the total DA taxa identified in the original and TphPMF-imputed datasets for four CRC datasets.
حسب: Xinyu Han (2237545)
منشور في: (2025)

The number of differentially abundant (DA) taxa identified in the raw datasets and the TphPMF-imputed datasets of two T2D datasets and four CRC datasets using six DA analysis methods, under an FDR threshold of 0.05.
حسب: Xinyu Han (2237545)
منشور في: (2025)

The schematic diagram of the principle of TphPMF imputing non-biological zeros at each hierarchical level.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Schematic of the TphPMF model.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Accuracy of cross-prediction classification (PR-AUC) results using two classification algorithms for the two CRC datasets by Yu et al. [
حسب: Xinyu Han (2237545)
منشور في: (2025)

Accuracy of cross-prediction classification (PR-AUC) results using two classification algorithms for the two T2D datasets by Qin et al. [
حسب: Xinyu Han (2237545)
منشور في: (2025)

Performance results of TphPMF in preserving the distributional features of taxa non-zero abundances.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Results of sample disease state prediction using SVM algorithm with DA taxa identified by DESeq2-phyloseq as features, before and after imputation by TphPMF.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Robustness analysis results for TphPMF.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Precision, recall, and F1 score of six DA methods with and without imputation using mbImpute, mbDenoise or TphPMF.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of the performance of TphPMF with other imputation methods in Simulation 1 and Simulation 2.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Accuracy of cross-prediction classification (PR-AUC) results using two classification algorithms for the two T2D datasets by Qin et al. [38] and Karlsson et al. [36].
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of Spearman correlations between the full-sample abundances and the original non-zero sample abundances before and after imputation with TphPMF, using Spearman correlation to define similarity, for all samples, “disease” samples, and control samples in 2 T2D datasets and 4 CRC datasets.
حسب: Xinyu Han (2237545)
منشور في: (2025)

The abundance distribution of three example taxa identified by DESeq2-phyloseq before imputation with TphPMF and not identified after imputation in the dataset of Yu et al. [41] and the dataset of Zeller et al. [42].
حسب: Xinyu Han (2237545)
منشور في: (2025)

Results of sample disease state prediction using XGBoost algorithm with DA taxa identified by DESeq2-phyloseq as features, before and after imputation by TphPMF.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Distribution of taxon p-values calculated by ANCOM-BC2, DESeq2_phyloseq and LOCOM before and after imputation with TphPMF.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Abundance distribution of four example taxa after the introduction of two outlier samples.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Precision, recall, and F1 score of six DA methods with and without imputation using mbImpute, mbDenoise or TphPMF in the case of 45 DA taxa.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Precision, recall, and F1 score of six DA methods with and without imputation using mbImpute, mbDenoise or TphPMF in the case of 20 DA taxa.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of runtime between TphPMF, mbImpute, and mbDenoise.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of the performance of TphPMF with other imputation methods in three Simulations (zero proportions: Simulation1: 75.5%; Simulation2: 76.9%; Simulation3: 77.9%).
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of the performance of TphPMF with other imputation methods in three Simulations (zero proportions: Simulation1: 71.5%; Simulation2: 74.3%; Simulation3: 75.1%).
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of the performance of TphPMF with other imputation methods in three Simulations (zero proportions: Simulation1: 62.8%; Simulation2: 68.5%; Simulation3: 69.6%).
حسب: Xinyu Han (2237545)
منشور في: (2025)

Comparison of the performance of TphPMF with other imputation methods in Simulation 3.
حسب: Xinyu Han (2237545)
منشور في: (2025)

Relationship between statistical power, sample size and log fold change. 1000 taxa, 100 samples per group and 100 simulations. log mean abundance = 5.
حسب: Michael Agronah (21022048)
منشور في: (2025)

Contour plot showing statistical power for various combinations of overall log mean abundance and log fold change. 1000 taxa, 100 samples per group and 100 simulations. Red points indicate simulated taxa with significant log fold change (that is, adjusted FDR-corrected <i>p</i>-value 40<i>%</i>); black points show simulated taxa where we failed to reject the null hypothesis (adjusted <i>p</i>-value 40<i>%</i>). Contour lines show the predicted statistical power for various combinations of log mean abundance and log fold change.
حسب: Michael Agronah (21022048)
منشور في: (2025)

Relationship between log fold changes and log mean abundance for three typical datasets. The unusual features in the plot (concentrations of points along symmetric curves above and below zero) in the first two panels correspond to taxa with zero counts across all subjects in either the control or the treatment group.
حسب: Michael Agronah (21022048)
منشور في: (2025)

ADATEST_results_for_all_settings.RData
حسب: Connie Nakasi Musisi (22031888)
منشور في: (2025)

Mixed nuts and microbiome - J Med Food-2023.pdf
حسب: Mee Young Hong (19728171)
منشور في: (2024)

Mixed nuts and microbiome - J Med Food-2023.pdf
حسب: Mee Young Hong (19728171)
منشور في: (2024)

Mixed nuts and microbiome - J Med Food-2023.pdf
حسب: Mee Young Hong (9853158)
منشور في: (2024)

meta2bseek database (GTDB r220)
حسب: ZHANG (18130402)
منشور في: (2025)

UHGG abundances across human gut metagenomes
حسب: Alex Almeida (19685953)
منشور في: (2025)

<b>Source data for "Integrating anthropogenic-pesticide interactions into a soil health-microbial index for sustainable agriculture at global scale"</b>
حسب: Nuohan Xu (20111580)
منشور في: (2024)

Comparison of average statistical power across all taxa and quantiles of taxon-by-taxon power estimates. Average power often overestimates the statistical power for most taxa and might not be a good metric for understanding the power to detect effects in a differential abundance study, hence the need to estimate power at the level of individual taxa.
حسب: Michael Agronah (21022048)
منشور في: (2025)

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