Microba Research Discovery Report

Taxonomic Profiles (Genus)

The charts below show the taxonomic composition of the analysed samples using different quantitative visualization techniques. Only the top most abundant genera are shown.

Areachart

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Barchart clustered within each group

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All features barchart clustered within each group

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Scaled heatmap of most abundant features ordered by study group

Features were filtered by mean abundance. Samples were first ordered by study group and then clustered within each study group. Abundances were scaled to a max value of 1. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

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Heatmap of most abundant features ordered by study group

Features were filtered by mean abundance. Samples were first ordered by study group and then clustered within each study group. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

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Scaled heatmap of all features

Profiles were clustered by hierarchical clustering. Abundances were scaled to a max value of 1. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

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Heatmap of all features

Profiles were clustered by hierarchical clustering. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

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Scaled heatmap of top most abundant features filtered by mean abundance

Profiles were clustered by hierarchical clustering. Abundances were scaled to a max value of 1. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

Click here to open full-sized image in new window.

Heatmap of top most abundant features filtered by mean abundance

Profiles were clustered by hierarchical clustering. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

Click here to open full-sized image in new window.

Scaled heatmap of top most abundant features filtered by max abundance

Profiles were clustered by hierarchical clustering. Abundances were scaled to a max value of 1. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

Click here to open full-sized image in new window.

Heatmap of top most abundant features filtered by max abundance

Profiles were clustered by hierarchical clustering. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

Click here to open full-sized image in new window.

Scaled heatmap of top most variable features

Profiles were clustered by hierarchical clustering. Abundances were scaled to a max value of 1. Color scale shows not-detected (white), and abundance ranging from low (blue) to high (yellow).

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Hierarchically clustered barchart

Profiles were clustered by hierarchical clustering.

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Interactive Barchart

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Microbial alpha diversity (genus)

This page provides an overview of the microbial alpha diversity of the analysed samples. Alpha diversity is measured by the Shannon index and species richnes. Richness simply quantifies the total number of genera present in each sample. Shannon index additionally accounts for relative abundance and evenness of the genera present and quantifies the entropy of microbial communties. Barcharts and boxplots present the mean diversity in each study group.

Methods:

Shannon diversity was compared using linear mixed effect regression, including Participant as a random effect (intercept), and Treatment as a fixed effect. Effect tested: Treatment. Richness was compared using linear mixed effect regression, including Participant as a random effect (intercept), and Treatment as a fixed effect. Effect tested: Treatment. Data was rarefied to 702268 reads.

Index: Richness

Index: Shannon index

Summary Table

Index	rarefiedTo	P lmer condition effect	Mean Pos	Mean Abundance	Median Abundance	Mean Treatmentpost_treatment	Median Treatmentpost_treatment	SD Treatmentpost_treatment	Mean Treatmentpre_treatment	Median Treatmentpre_treatment	SD Treatmentpre_treatment	Fold Change Log2(Treatmentpre_treatment/Treatmentpost_treatment)	Positive samples	Positive Treatmentpost_treatment	Positive Treatmentpre_treatment	Positive_Treatmentpost_treatment_percent	Positive_Treatmentpre_treatment_percent
Shannon	702268	0.12	2.6	2.6	2.6	2.6	2.6	0.29	2.7	2.5	0.48	0.054	38 / 38 (100%)	19 / 19 (100%)	19 / 19 (100%)	1	1
Richness	702268	0.015	33	33	28	30	27	11	35	28	16	0.22	38 / 38 (100%)	19 / 19 (100%)	19 / 19 (100%)	1	1

Download diversity values in csv format . On some platforms (including Windows) you may need to change the suffix from .txt or .html to .csv before opening the file in a spreadsheet program, like Excel.

Clustering and ordination (genus)

Taxonomic profiles were analyzed using supervised and unsupervised multivariate methods. Profiles were ordinated using the unsupervised methods Principal Coordinates Analysis (PCoA), Non-Metric Multidimensional Scaling (NMDS) and Principal Component Analysis (PCA). PCoA and NMDS are related to PCA, but take dissimlarity matrices as input. PCoA and NMDS both attempt to represent the pairwise dissimlarities between samples in low dimensional space as close as possible. NMDS is a rank-based approach and therefore less effected by outliers.

The supervised methods Adonis and Redundancy analysis (RDA) were used to assess if variance in microbial community composition can be attributed to the study condition. NMDS, PCoA and Adonis were run on Bray-Curtis dissimilarities. A short introduction of the used methods can be found at the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME). Sparse Partial Least Square Discriminant Analysis (sPLS-DA) from the MixMc package was additionaly used to extract features associated with the study condition.

Unsupervised ordination

Interactive PCA (clr transformed)

Please click here to view an interactive 3D PCA.

Univariate analysis of genus abundance

Differentially abundant genera were identified by ANOVA or LMER (linear mixed effect regression) of clr transformed relative abudances, Fisher's exact test and/or ALDEx2 (on genera read counts). Fisher's exact test is used to test for differences in the detection rate, i.e. number of samples in which each genus has been detected.

LMER is used for repeated measures data, using random effects to control for correlation between samples from the same subject. Fixed effects are included for treatment groups, time, and treatment over time, where appropriate. The LMER P values correspond to a nested model test of the significance of including the corresponding fixed effect.

ALDEx2 uses subsampling (Bayesian sampling) to estimate the underlying technical variation. For each subsample instance, center log-ratio transformed data is statistically compared across study groups and computed P values are corrected for multiple testing using the Benjamini–Hochberg procedure. The expected P value (mean P value) is reported, which are those that would likely have been observed if the same samples had been run multiple times. The expected values are reported for both the distribution of P values and for the distribution of Benjamini–Hochberg corrected values.

Taxon	GTDB taxonomy	P lmer condition effect (sqrt)	FDR lmer condition effect (sqrt)	Pbonf lmer condition effect (sqrt)	P lmer condition effect (clr)	FDR lmer condition effect (clr)	Pbonf lmer condition effect (clr)	Mean Pos	Mean Abundance	Median Abundance	Mean Treatmentpost_treatment	Median Treatmentpost_treatment	SD Treatmentpost_treatment	Mean Treatmentpre_treatment	Median Treatmentpre_treatment	SD Treatmentpre_treatment	Fold Change Log2(Treatmentpre_treatment/Treatmentpost_treatment)	Positive samples	Positive Treatmentpost_treatment	Positive Treatmentpre_treatment	Positive_Treatmentpost_treatment_percent	Positive_Treatmentpre_treatment_percent
Acetatifactor	Acetatifactor	0.32	0.61	1	0.43	0.78	1	0.6	0.14	0	0.2	0	0.43	0.085	0	0.21	-1.2	9 / 38 (24%)	5 / 19 (26%)	4 / 19 (21%)	0.263	0.211
Adlercreutzia	Adlercreutzia	0.27	0.6	1	0.3	0.75	1	0.22	0.034	0	0.029	0	0.099	0.039	0	0.088	0.43	6 / 38 (16%)	2 / 19 (11%)	4 / 19 (21%)	0.105	0.211
Agathobacter	Agathobacter	0.85	0.96	1	0.86	0.95	1	10	9.6	7.5	9.9	7.2	8.1	9.3	7.9	7.1	-0.09	35 / 38 (92%)	17 / 19 (89%)	18 / 19 (95%)	0.895	0.947
Agathobaculum	Agathobaculum	0.025	0.3	1	0.015	0.34	1	0.68	0.18	0	0.29	0	0.4	0.072	0	0.22	-2	10 / 38 (26%)	8 / 19 (42%)	2 / 19 (11%)	0.421	0.105
Akkermansia	Akkermansia	0.33	0.61	1	0.88	0.95	1	1.4	0.37	0	0.24	0	0.59	0.5	0	0.97	1.1	10 / 38 (26%)	5 / 19 (26%)	5 / 19 (26%)	0.263	0.263
Alistipes	Alistipes	0.32	0.61	1	0.25	0.71	1	1.7	0.52	0	0.52	0	1.6	0.52	0	0.96	0	12 / 38 (32%)	5 / 19 (26%)	7 / 19 (37%)	0.263	0.368
Alistipes_A	Alistipes_A	0.15	0.57	1	0.64	0.83	1	0.21	0.017	0	0.0071	0	0.031	0.026	0	0.1	1.9	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Anaerostipes	Anaerostipes	0.015	0.3	1	0.4	0.76	1	3.6	3.5	2.9	4.4	4.2	3.4	2.5	1.9	1.7	-0.82	37 / 38 (97%)	18 / 19 (95%)	19 / 19 (100%)	0.947	1
Bacteroides	Bacteroides	0.21	0.6	1	0.28	0.73	1	5.2	2.2	0	3	0	7.4	1.4	0	2.5	-1.1	16 / 38 (42%)	9 / 19 (47%)	7 / 19 (37%)	0.474	0.368
Bacteroides_B	Bacteroides_B	0.96	0.97	1	0.39	0.76	1	4.3	1.5	0	1.9	0	5.2	1.1	0	2.1	-0.79	13 / 38 (34%)	5 / 19 (26%)	8 / 19 (42%)	0.263	0.421
Barnesiella	Barnesiella	0.25	0.6	1	0.53	0.8	1	0.31	0.025	0	0.0066	0	0.029	0.043	0	0.14	2.7	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Bifidobacterium	Bifidobacterium	0.33	0.61	1	0.062	0.45	1	9.4	8.2	4.6	7.4	4.6	7.6	8.9	4.7	15	0.27	33 / 38 (87%)	17 / 19 (89%)	16 / 19 (84%)	0.895	0.842
Blautia	Blautia	0.29	0.61	1	0.21	0.69	1	1.6	0.25	0	0.36	0	1.2	0.15	0	0.41	-1.3	6 / 38 (16%)	3 / 19 (16%)	3 / 19 (16%)	0.158	0.158
Blautia_A	Blautia_A	0.76	0.92	1	0.38	0.76	1	14	14	13	14	11	7.8	14	14	6.6	0	38 / 38 (100%)	19 / 19 (100%)	19 / 19 (100%)	1	1
Butyrivibrio_A	Butyrivibrio_A	0.16	0.57	1	0.37	0.76	1	1.2	0.098	0	0.018	0	0.079	0.18	0	0.54	3.3	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-103	CAG-103	0.96	0.97	1	0.38	0.76	1	0.81	0.3	0	0.26	0	0.38	0.33	0	0.65	0.34	14 / 38 (37%)	8 / 19 (42%)	6 / 19 (32%)	0.421	0.316
CAG-110	CAG-110	0.28	0.6	1	0.36	0.76	1	0.75	0.099	0	0.15	0	0.49	0.053	0	0.17	-1.5	5 / 38 (13%)	3 / 19 (16%)	2 / 19 (11%)	0.158	0.105
CAG-127	CAG-127	0.96	0.97	1	0.85	0.95	1	0.54	0.071	0	0.089	0	0.34	0.054	0	0.13	-0.72	5 / 38 (13%)	2 / 19 (11%)	3 / 19 (16%)	0.105	0.158
CAG-138 MIC9630	CAG-138 MIC9630	0.038	0.3	1	0.071	0.45	1	1.3	0.17	0	0.045	0	0.2	0.3	0	0.65	2.7	5 / 38 (13%)	1 / 19 (5.3%)	4 / 19 (21%)	0.0526	0.211
CAG-1427	CAG-1427	0.87	0.97	1	0.87	0.95	1	0.4	0.095	0	0.1	0	0.24	0.091	0	0.17	-0.14	9 / 38 (24%)	4 / 19 (21%)	5 / 19 (26%)	0.211	0.263
CAG-145	CAG-145	0.41	0.7	1	0.83	0.95	1	0.27	0.022	0	0.021	0	0.093	0.022	0	0.081	0.067	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-170	CAG-170	0.038	0.3	1	0.022	0.34	1	0.9	0.14	0	0.0063	0	0.027	0.28	0	0.9	5.5	6 / 38 (16%)	1 / 19 (5.3%)	5 / 19 (26%)	0.0526	0.263
CAG-177	CAG-177	0.5	0.78	1	0.13	0.57	1	0.98	0.18	0	0.18	0	0.39	0.18	0	0.55	0	7 / 38 (18%)	4 / 19 (21%)	3 / 19 (16%)	0.211	0.158
CAG-217	CAG-217	0.89	0.97	1	0.24	0.69	1	1.6	0.42	0	0.38	0	0.71	0.45	0	0.94	0.24	10 / 38 (26%)	6 / 19 (32%)	4 / 19 (21%)	0.316	0.211
CAG-245	CAG-245	0.27	0.6	1	0.38	0.76	1	0.48	0.05	0	0.02	0	0.085	0.081	0	0.24	2	4 / 38 (11%)	1 / 19 (5.3%)	3 / 19 (16%)	0.0526	0.158
CAG-269	CAG-269	0.78	0.94	1	0.16	0.66	1	0.77	0.082	0	0.095	0	0.35	0.068	0	0.25	-0.48	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
CAG-274	CAG-274	0.057	0.42	1	0.04	0.37	1	0.5	0.11	0	0.16	0	0.35	0.048	0	0.14	-1.7	8 / 38 (21%)	5 / 19 (26%)	3 / 19 (16%)	0.263	0.158
CAG-302	CAG-302	0.14	0.57	1	0.48	0.8	1	0.84	0.16	0	0.097	0	0.24	0.21	0	0.51	1.1	7 / 38 (18%)	3 / 19 (16%)	4 / 19 (21%)	0.158	0.211
CAG-313	CAG-313	0.17	0.58	1	0.59	0.82	1	0.46	0.037	0	0.023	0	0.1	0.05	0	0.18	1.1	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-314	CAG-314	0.22	0.6	1	0.5	0.8	1	0.32	0.025	0	0.0075	0	0.033	0.043	0	0.13	2.5	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-354	CAG-354	0.92	0.97	1	0.93	0.96	1	0.41	0.054	0	0.057	0	0.17	0.051	0	0.14	-0.16	5 / 38 (13%)	2 / 19 (11%)	3 / 19 (16%)	0.105	0.158
CAG-41	CAG-41	0.033	0.3	1	0.035	0.36	1	0.79	0.37	0	0.47	0.37	0.7	0.28	0	0.5	-0.75	18 / 38 (47%)	11 / 19 (58%)	7 / 19 (37%)	0.579	0.368
CAG-417	CAG-417	0.68	0.87	1	0.24	0.69	1	1.2	0.092	0	0.091	0	0.29	0.094	0	0.41	0.047	3 / 38 (7.9%)	2 / 19 (11%)	1 / 19 (5.3%)	0.105	0.0526
CAG-452	CAG-452	0.24	0.6	1	0.55	0.81	1	0.29	0.023	0	0.012	0	0.051	0.034	0	0.1	1.5	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-460	CAG-460	0.21	0.6	1	0.45	0.79	1	2	0.16	0	0.069	0	0.3	0.25	0	0.76	1.9	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-485	CAG-485	0.7	0.87	1	0.74	0.89	1	0.49	0.039	0	0.043	0	0.19	0.035	0	0.1	-0.3	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-533	CAG-533	0.19	0.6	1	0.43	0.78	1	2	0.15	0	0.055	0	0.24	0.25	0	0.76	2.2	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-557	CAG-557	0.46	0.76	1	0.63	0.83	1	0.63	0.049	0	0.043	0	0.19	0.056	0	0.17	0.38	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-56	CAG-56	0.51	0.78	1	0.23	0.69	1	0.96	0.53	0.26	0.54	0.39	0.62	0.53	0	0.88	-0.027	21 / 38 (55%)	12 / 19 (63%)	9 / 19 (47%)	0.632	0.474
CAG-628	CAG-628	0.22	0.6	1	0.52	0.8	1	0.47	0.037	0	0.018	0	0.08	0.056	0	0.17	1.6	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
CAG-83	CAG-83	0.018	0.3	1	0.029	0.36	1	1.7	0.44	0	0.21	0	0.56	0.67	0	1.1	1.7	10 / 38 (26%)	3 / 19 (16%)	7 / 19 (37%)	0.158	0.368
CAG-877	CAG-877	0.32	0.61	1	0.08	0.48	1	0.41	0.043	0	0.03	0	0.095	0.056	0	0.2	0.9	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
Clostridium	Clostridium	0.68	0.87	1	0.59	0.82	1	0.64	0.15	0	0.082	0	0.16	0.22	0	0.71	1.4	9 / 38 (24%)	5 / 19 (26%)	4 / 19 (21%)	0.263	0.211
Collinsella	Collinsella	0.14	0.57	1	0.23	0.69	1	1.9	1.3	0.65	0.91	0.44	1	1.6	0.68	2.1	0.81	26 / 38 (68%)	12 / 19 (63%)	14 / 19 (74%)	0.632	0.737
Coprococcus	Coprococcus	0.92	0.97	1	0.51	0.8	1	2	0.91	0	0.97	0	1.3	0.86	0	1.4	-0.17	17 / 38 (45%)	8 / 19 (42%)	9 / 19 (47%)	0.421	0.474
Coprococcus_A	Coprococcus_A	0.6	0.87	1	0.28	0.73	1	0.49	0.1	0	0.11	0	0.22	0.093	0	0.22	-0.24	8 / 38 (21%)	5 / 19 (26%)	3 / 19 (16%)	0.263	0.158
Coprococcus_B	Coprococcus_B	0.097	0.54	1	0.28	0.73	1	0.76	0.56	0.59	0.46	0.52	0.42	0.65	0.63	0.5	0.5	28 / 38 (74%)	13 / 19 (68%)	15 / 19 (79%)	0.684	0.789
Dialister	Dialister	0.47	0.76	1	0.98	0.99	1	1.6	0.69	0	0.66	0	1.1	0.71	0	1	0.11	16 / 38 (42%)	8 / 19 (42%)	8 / 19 (42%)	0.421	0.421
Dorea	Dorea	0.23	0.6	1	0.43	0.78	1	1.5	1.4	1.2	1.3	1.1	0.95	1.5	1.4	1.2	0.21	35 / 38 (92%)	18 / 19 (95%)	17 / 19 (89%)	0.947	0.895
Duncaniella	Duncaniella	0.66	0.87	1	0.73	0.89	1	0.49	0.039	0	0.041	0	0.18	0.036	0	0.11	-0.19	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Eisenbergiella	Eisenbergiella	0.07	0.45	1	0.12	0.57	1	1.6	0.21	0	0.087	0	0.38	0.34	0	1.4	2	5 / 38 (13%)	1 / 19 (5.3%)	4 / 19 (21%)	0.0526	0.211
ER4	ER4	0.89	0.97	1	0.2	0.69	1	0.49	0.077	0	0.069	0	0.15	0.085	0	0.26	0.3	6 / 38 (16%)	4 / 19 (21%)	2 / 19 (11%)	0.211	0.105
Erysipelatoclostridium	Erysipelatoclostridium	0.034	0.3	1	0.036	0.36	1	0.88	0.74	0.48	0.58	0.43	0.68	0.89	0.52	1.1	0.62	32 / 38 (84%)	14 / 19 (74%)	18 / 19 (95%)	0.737	0.947
Escherichia	Escherichia	0.27	0.6	1	0.56	0.81	1	2.2	0.17	0	0.14	0	0.6	0.21	0	0.7	0.58	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Eubacterium_E	Eubacterium_E	0.9	0.97	1	0.84	0.95	1	2.1	1.9	2	2	2	1.1	1.8	2	1.1	-0.15	34 / 38 (89%)	17 / 19 (89%)	17 / 19 (89%)	0.895	0.895
Eubacterium_F	Eubacterium_F	0.8	0.95	1	0.93	0.96	1	0.89	0.16	0	0.23	0	0.74	0.1	0	0.21	-1.2	7 / 38 (18%)	3 / 19 (16%)	4 / 19 (21%)	0.158	0.211
Eubacterium_G	Eubacterium_G	0.02	0.3	1	0.014	0.34	1	0.55	0.14	0	0.079	0	0.25	0.21	0	0.33	1.4	10 / 38 (26%)	2 / 19 (11%)	8 / 19 (42%)	0.105	0.421
Eubacterium_I	Eubacterium_I	0.16	0.57	1	0.2	0.69	1	0.72	0.23	0	0.15	0	0.28	0.31	0	0.63	1	12 / 38 (32%)	5 / 19 (26%)	7 / 19 (37%)	0.263	0.368
Eubacterium_R	Eubacterium_R	0.31	0.61	1	0.49	0.8	1	1.4	0.29	0	0.24	0	0.61	0.34	0	0.61	0.5	8 / 38 (21%)	3 / 19 (16%)	5 / 19 (26%)	0.158	0.263
F23-B02	F23-B02	0.13	0.57	1	0.2	0.69	1	0.73	0.077	0	0.025	0	0.11	0.13	0	0.32	2.4	4 / 38 (11%)	1 / 19 (5.3%)	3 / 19 (16%)	0.0526	0.158
Faecalibacterium	Faecalibacterium	0.62	0.87	1	0.41	0.78	1	6.2	6.2	5	6.6	6.3	4.3	5.7	4.6	3.6	-0.21	38 / 38 (100%)	19 / 19 (100%)	19 / 19 (100%)	1	1
Faecalicatena	Faecalicatena	0.00011	0.011	0.011	0.013	0.34	1	1.7	1.1	0.59	0.66	0.21	0.92	1.5	0.68	1.8	1.2	25 / 38 (66%)	10 / 19 (53%)	15 / 19 (79%)	0.526	0.789
Fusicatenibacter	Fusicatenibacter	0.37	0.67	1	0.063	0.45	1	4.5	4	2.7	4.2	3	3.8	3.8	2.6	4.1	-0.14	34 / 38 (89%)	17 / 19 (89%)	17 / 19 (89%)	0.895	0.895
GCA-900066135	GCA-900066135	0.029	0.3	1	0.011	0.34	1	0.31	0.072	0	0.098	0	0.15	0.047	0	0.18	-1.1	9 / 38 (24%)	7 / 19 (37%)	2 / 19 (11%)	0.368	0.105
Gemmiger	Gemmiger	0.28	0.6	1	0.61	0.82	1	2.4	2.2	1.4	2.5	1.9	2.7	1.8	1.3	1.8	-0.47	34 / 38 (89%)	17 / 19 (89%)	17 / 19 (89%)	0.895	0.895
Holdemanella	Holdemanella	0.93	0.97	1	0.067	0.45	1	2.6	0.41	0	0.4	0	1	0.42	0	1.1	0.07	6 / 38 (16%)	3 / 19 (16%)	3 / 19 (16%)	0.158	0.158
Intestinibacter	Intestinibacter	0.97	0.97	1	0.82	0.95	1	0.26	0.054	0	0.054	0	0.12	0.054	0	0.12	0	8 / 38 (21%)	4 / 19 (21%)	4 / 19 (21%)	0.211	0.211
KLE1615	KLE1615	0.42	0.71	1	0.5	0.8	1	1.2	0.55	0	0.52	0	0.76	0.58	0	0.74	0.16	17 / 38 (45%)	8 / 19 (42%)	9 / 19 (47%)	0.421	0.474
Lachnospira	Lachnospira	0.62	0.87	1	0.4	0.76	1	0.99	0.49	0.15	0.51	0	0.77	0.48	0.31	0.63	-0.087	19 / 38 (50%)	8 / 19 (42%)	11 / 19 (58%)	0.421	0.579
Lactobacillus_B	Lactobacillus_B	0.11	0.55	1	0.057	0.45	1	1.3	0.13	0	0.25	0	0.68	0.022	0	0.098	-3.5	4 / 38 (11%)	3 / 19 (16%)	1 / 19 (5.3%)	0.158	0.0526
Lactobacillus_H	Lactobacillus_H	0.15	0.57	1	0.12	0.57	1	0.67	0.053	0	0.098	0	0.3	0.0078	0	0.034	-3.7	3 / 38 (7.9%)	2 / 19 (11%)	1 / 19 (5.3%)	0.105	0.0526
Megamonas	Megamonas	0.83	0.96	1	0.88	0.95	1	0.46	0.049	0	0.063	0	0.19	0.035	0	0.13	-0.85	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
Methanobrevibacter_A	Methanobrevibacter_A	0.52	0.78	1	0.92	0.96	1	0.91	0.095	0	0.051	0	0.15	0.14	0	0.42	1.5	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
Monoglobus	Monoglobus	0.062	0.42	1	0.12	0.57	1	0.2	0.038	0	0.0091	0	0.027	0.066	0	0.13	2.9	7 / 38 (18%)	2 / 19 (11%)	5 / 19 (26%)	0.105	0.263
NK3B98	NK3B98	0.4	0.69	1	0.7	0.88	1	0.2	0.016	0	0.012	0	0.054	0.019	0	0.057	0.66	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Oscillibacter	Oscillibacter	0.14	0.57	1	0.13	0.57	1	0.57	0.06	0	0.11	0	0.31	0.0072	0	0.031	-3.9	4 / 38 (11%)	3 / 19 (16%)	1 / 19 (5.3%)	0.158	0.0526
Oxalobacter	Oxalobacter	0.23	0.6	1	0.13	0.57	1	0.11	0.0083	0	0.011	0	0.036	0.0051	0	0.022	-1.1	3 / 38 (7.9%)	2 / 19 (11%)	1 / 19 (5.3%)	0.105	0.0526
Parabacteroides	Parabacteroides	0.28	0.6	1	0.52	0.8	1	0.62	0.11	0	0.096	0	0.36	0.13	0	0.33	0.44	7 / 38 (18%)	3 / 19 (16%)	4 / 19 (21%)	0.158	0.211
Parasutterella	Parasutterella	0.51	0.78	1	0.51	0.8	1	0.37	0.039	0	0.059	0	0.19	0.019	0	0.061	-1.6	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
Phascolarctobacterium	Phascolarctobacterium	0.031	0.3	1	0.37	0.76	1	0.82	0.19	0	0.15	0	0.49	0.24	0	0.62	0.68	9 / 38 (24%)	4 / 19 (21%)	5 / 19 (26%)	0.211	0.263
Prevotella	Prevotella	0.49	0.78	1	0.9	0.96	1	5.9	1.2	0	2.1	0	5.4	0.41	0	0.87	-2.4	8 / 38 (21%)	4 / 19 (21%)	4 / 19 (21%)	0.211	0.211
QAMH01	QAMH01	0.27	0.6	1	0.54	0.81	1	0.5	0.039	0	0.022	0	0.094	0.057	0	0.17	1.4	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Romboutsia	Romboutsia	0.83	0.96	1	0.85	0.95	1	0.73	0.23	0	0.2	0	0.35	0.26	0	0.51	0.38	12 / 38 (32%)	6 / 19 (32%)	6 / 19 (32%)	0.316	0.316
Roseburia	Roseburia	0.0093	0.3	0.94	0.023	0.34	1	0.74	0.25	0	0.1	0	0.22	0.4	0	0.53	2	13 / 38 (34%)	4 / 19 (21%)	9 / 19 (47%)	0.211	0.474
Ruminiclostridium_C	Ruminiclostridium_C	0.076	0.46	1	0.13	0.57	1	0.23	0.08	0	0.061	0	0.13	0.1	0	0.13	0.71	13 / 38 (34%)	5 / 19 (26%)	8 / 19 (42%)	0.263	0.421
Ruminiclostridium_E	Ruminiclostridium_E	0.1	0.54	1	0.18	0.69	1	1.2	0.13	0	0.041	0	0.18	0.22	0	0.59	2.4	4 / 38 (11%)	1 / 19 (5.3%)	3 / 19 (16%)	0.0526	0.158
Ruminococcus_A	Ruminococcus_A	0.95	0.97	1	0.59	0.82	1	0.96	0.43	0	0.42	0	0.67	0.43	0	0.83	0.034	17 / 38 (45%)	9 / 19 (47%)	8 / 19 (42%)	0.474	0.421
Ruminococcus_C	Ruminococcus_C	0.56	0.83	1	0.32	0.76	1	1.1	0.48	0	0.48	0	0.55	0.48	0	0.93	0	17 / 38 (45%)	9 / 19 (47%)	8 / 19 (42%)	0.474	0.421
Ruminococcus_D	Ruminococcus_D	0.64	0.87	1	0.99	0.99	1	2.6	1.3	0.11	1.5	0	2.6	1	0.22	1.5	-0.58	19 / 38 (50%)	9 / 19 (47%)	10 / 19 (53%)	0.474	0.526
Ruminococcus_E	Ruminococcus_E	0.73	0.9	1	0.72	0.89	1	4.4	3.2	2.8	3	2.6	3.4	3.4	3.7	3.7	0.18	28 / 38 (74%)	13 / 19 (68%)	15 / 19 (79%)	0.684	0.789
Senegalimassilia	Senegalimassilia	0.38	0.67	1	0.7	0.88	1	0.31	0.025	0	0.019	0	0.083	0.031	0	0.092	0.71	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
Streptococcus	Streptococcus	0.67	0.87	1	0.33	0.76	1	1	0.5	0	0.48	0.31	0.66	0.51	0	1.1	0.087	18 / 38 (47%)	10 / 19 (53%)	8 / 19 (42%)	0.526	0.421
TF01-11	TF01-11	0.7	0.87	1	0.73	0.89	1	0.33	0.07	0	0.09	0	0.23	0.05	0	0.12	-0.85	8 / 38 (21%)	4 / 19 (21%)	4 / 19 (21%)	0.211	0.211
Turicibacter	Turicibacter	0.38	0.67	1	0.68	0.88	1	0.22	0.017	0	0.0079	0	0.034	0.027	0	0.096	1.8	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
UBA11524	UBA11524	0.23	0.6	1	0.56	0.81	1	1.5	0.12	0	0.082	0	0.36	0.15	0	0.5	0.87	3 / 38 (7.9%)	1 / 19 (5.3%)	2 / 19 (11%)	0.0526	0.105
UBA11774	UBA11774	0.81	0.95	1	0.23	0.69	1	1.3	0.37	0	0.3	0	0.6	0.44	0	1.1	0.55	11 / 38 (29%)	6 / 19 (32%)	5 / 19 (26%)	0.316	0.263
UBA1191	UBA1191	0.61	0.87	1	0.61	0.82	1	0.61	0.064	0	0.078	0	0.27	0.05	0	0.19	-0.64	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
UBA1394	UBA1394	0.65	0.87	1	0.97	0.99	1	0.46	0.06	0	0.082	0	0.25	0.039	0	0.1	-1.1	5 / 38 (13%)	2 / 19 (11%)	3 / 19 (16%)	0.105	0.158
UBA1417	UBA1417	0.0095	0.3	0.95	0.016	0.34	1	0.61	0.11	0	0.024	0	0.1	0.2	0	0.36	3.1	7 / 38 (18%)	1 / 19 (5.3%)	6 / 19 (32%)	0.0526	0.316
UBA1691	UBA1691	0.21	0.6	1	0.27	0.73	1	1	0.11	0	0.086	0	0.31	0.13	0	0.4	0.6	4 / 38 (11%)	2 / 19 (11%)	2 / 19 (11%)	0.105	0.105
UBA1777	UBA1777	0.16	0.57	1	0.37	0.76	1	0.81	0.11	0	0.052	0	0.21	0.16	0	0.42	1.6	5 / 38 (13%)	2 / 19 (11%)	3 / 19 (16%)	0.105	0.158
UBA7160	UBA7160	0.66	0.87	1	0.92	0.96	1	0.51	0.13	0	0.13	0	0.32	0.14	0	0.36	0.11	10 / 38 (26%)	5 / 19 (26%)	5 / 19 (26%)	0.263	0.263

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Methods:

P lmer condition effect (sqrt): Differentially abundant species were identified by linear mixed effect regression without confounders. Random effects: Participant (intercept). Fixed effects: Treatment. Effect tested: Treatment.

P lmer condition effect (clr): Differentially abundant species were identified by linear mixed effect regression without confounders. Random effects: Participant (intercept). Fixed effects: Treatment. Effect tested: Treatment.

Glossary:

clr: Centered log-ratio transformation. P Welch's ANOVA (sqrt): Welch's ANOVA p-values (Anova was run on sqrt transformed abundances). It is an alternative to the classic ANOVA and can be used even if the samples have unequal variances and/or unequal sample sizes. P Welch's t-test (sqrt): Welch's T-test p-values (run on sqrt transformed abundances). It is an alternative to the classic Student's t-test and is more reliable if the data violates the assumption of homogeneity of variances and/or if the study conditions have unequal sample sizes. P Welch's ANOVA (clr): Welch's ANOVA p-values (Anova was run on clr transformed abundances). It is an alternative to the classic ANOVA and can be used even if the samples have unequal variances and/or unequal sample sizes. P Welch's t-test (clr): Welch's T-test p-values (run on clr transformed abundances). It is an alternative to the classic Student's t-test and is more reliable if the data violates the assumption of homogeneity of variances and/or if the study conditions have unequal sample sizes. P lmer XXX (clr): P-value of Linear Mixed-Effects Regression on clr transformed abundances, testing significance of XXX effect. Varying intercepts per subjects are used to control for repeated measures. Pbonf: Bonferroni corrected p-value. FDR: False Discovery Rate q-value. Mean Pos: Mean abundance in positive samples. Positive samples: The number and percentage of samples in which each genus has been detected. Positive XXX: The number and percentage of positive samples in study group XXX. Positive_XXX_percent: Percentage of positive samples in study group XXX. P Welch's t-test (Aldex2): Expected P value of Welch’s t-test computed by Aldex2. FDR Welch's t-test (Aldex2): Expected Benjamini-Hochberg corrected P value for Welch’s t-test. P Wilcoxon rank test (Aldex2): Expected P value of Wilcoxon rank test computed by Aldex2. FDR Wilcoxon rank test (Aldex2): Expected Benjamini-Hochberg corrected P value of Wilcoxon test. P Kruskal-Wallace test (Aldex2): Expected P value of Kruskal-Wallace test. FDR Kruskal-Wallace test (Aldex2): Expected Benjamini-Hochberg corrected P value of Kruskal-Wallace test. P GLM test (Aldex2): Expected P value of generalized linear model. FDR GLM test (Aldex2): Expected Benjamini-Hochberg corrected P value of generalized linear model.

Differentially abundant taxa (genus)

The following plots present the distribution of the top most differentially abundant genera across all applied statistical analysis. Plots are ordered alphabetically.

Glossary:

"Rel. Abundance": Relative abundance data; "Rel. Abundance (sqrt)": sqrt (Hellinger) transformed relative abundances; "Rel. Abundance (clr)": centered log-ratio (clr) transformed read counts.