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 a standard t-test. Richness was compared using a standard t-test. Data was rarefied to 702268 reads.

Index: Richness

Index: Shannon index

Summary Table

Index	rarefiedTo	P Welch's t-test	Mean Pos	Mean Abundance	Median Abundance	Mean Post_Treatment_Fibre_Intakehigh	Median Post_Treatment_Fibre_Intakehigh	SD Post_Treatment_Fibre_Intakehigh	Mean Post_Treatment_Fibre_Intakelow	Median Post_Treatment_Fibre_Intakelow	SD Post_Treatment_Fibre_Intakelow	Fold Change Log2(Post_Treatment_Fibre_Intakelow/Post_Treatment_Fibre_Intakehigh)	Positive samples	Positive Post_Treatment_Fibre_Intakehigh	Positive Post_Treatment_Fibre_Intakelow	Positive_Post_Treatment_Fibre_Intakehigh_percent	Positive_Post_Treatment_Fibre_Intakelow_percent
Shannon	702268	0.73	2.6	2.6	2.6	2.6	2.5	0.19	2.5	2.6	0.44	-0.057	18 / 18 (100%)	11 / 11 (100%)	7 / 7 (100%)	1	1
Richness	702268	0.67	30	30	26	29	26	6.9	32	28	16	0.14	18 / 18 (100%)	11 / 11 (100%)	7 / 7 (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 PCoA.

Please click here to view an interactive 3D PCA.

Supervised Analysis

sPLS-DA

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 Welch's t-test (sqrt)	FDR Welch's t-test (sqrt)	Pbonf Welch's t-test (sqrt)	Cohen's d Welch's t-test (sqrt)	P Welch's t-test (clr)	FDR Welch's t-test (clr)	Pbonf Welch's t-test (clr)	Cohen's d Welch's t-test (clr)	P Fisher's exact test	FDR Fisher's exact test	Pbonf Fisher's exact test	P Welch's t-test (ALDEx2)	FDR Welch's t-test (ALDEx2)	P Wilcoxon rank test (ALDEx2)	FDR Wilcoxon rank test (ALDEx2)	Mean Pos	Mean Abundance	Median Abundance	Mean Post_Treatment_Fibre_Intakehigh	Median Post_Treatment_Fibre_Intakehigh	SD Post_Treatment_Fibre_Intakehigh	Mean Post_Treatment_Fibre_Intakelow	Median Post_Treatment_Fibre_Intakelow	SD Post_Treatment_Fibre_Intakelow	Fold Change Log2(Post_Treatment_Fibre_Intakelow/Post_Treatment_Fibre_Intakehigh)	Positive samples	Positive Post_Treatment_Fibre_Intakehigh	Positive Post_Treatment_Fibre_Intakelow	Positive_Post_Treatment_Fibre_Intakehigh_percent	Positive_Post_Treatment_Fibre_Intakelow_percent
Acetatifactor	Acetatifactor	0.15	0.93	1	-0.94	0.18	0.85	1	-0.82	0.25	1	1	0.2	0.81	0.27	0.83	0.86	0.19	0	0.043	0	0.14	0.42	0	0.64	3.3	4 / 18 (22%)	1 / 11 (9.1%)	3 / 7 (43%)	0.0909	0.429
Agathobacter	Agathobacter	0.15	0.93	1	0.84	0.12	0.85	1	1.1	0.14	1	1	0.12	0.8	0.13	0.8	11	9.7	7	12	9.5	8.4	6.7	3.9	7.6	-0.84	16 / 18 (89%)	11 / 11 (100%)	5 / 7 (71%)	1	0.714
Agathobaculum	Agathobaculum	0.084	0.93	1	0.82	0.057	0.85	1	0.9	0.15	1	1	0.094	0.8	0.16	0.8	0.69	0.27	0	0.38	0.36	0.44	0.092	0	0.24	-2	7 / 18 (39%)	6 / 11 (55%)	1 / 7 (14%)	0.545	0.143
Akkermansia	Akkermansia	0.31	0.93	1	-0.58	0.28	0.85	1	-0.57	0.33	1	1	0.27	0.82	0.3	0.84	0.92	0.26	0	0.13	0	0.37	0.45	0	0.85	1.8	5 / 18 (28%)	2 / 11 (18%)	3 / 7 (43%)	0.182	0.429
Alistipes	Alistipes	0.78	0.95	1	-0.13	0.36	0.85	1	-0.46	0.33	1	1	0.29	0.83	0.33	0.85	2	0.55	0	0.67	0	2	0.37	0	0.53	-0.86	5 / 18 (28%)	2 / 11 (18%)	3 / 7 (43%)	0.182	0.429
Anaerostipes	Anaerostipes	0.73	0.95	1	0.21	0.3	0.85	1	0.68	0.39	1	1	0.29	0.83	0.41	0.87	4.8	4.5	4.6	4.3	4.2	2	4.8	5	5.3	0.16	17 / 18 (94%)	11 / 11 (100%)	6 / 7 (86%)	1	0.857
Bacteroides	Bacteroides	0.27	0.93	1	-0.66	0.19	0.85	1	-0.67	0.33	1	1	0.17	0.8	0.25	0.83	6.2	3.1	0.19	1.3	0	2.1	6	1.5	12	2.2	9 / 18 (50%)	4 / 11 (36%)	5 / 7 (71%)	0.364	0.714
Bacteroides_B	Bacteroides_B	0.3	0.93	1	0.43	0.68	0.94	1	0.19	1	1	1	0.79	0.94	0.66	0.92	7	2	0	3	0	6.7	0.33	0	0.79	-3.2	5 / 18 (28%)	3 / 11 (27%)	2 / 7 (29%)	0.273	0.286
Bifidobacterium	Bifidobacterium	0.092	0.93	1	0.85	0.16	0.85	1	0.93	0.14	1	1	0.19	0.81	0.32	0.85	8.5	7.6	4.9	9.8	6.3	8.9	4	4.2	4.3	-1.3	16 / 18 (89%)	11 / 11 (100%)	5 / 7 (71%)	1	0.714
Blautia	Blautia	0.37	0.95	1	-0.56	0.41	0.87	1	-0.47	0.53	1	1	0.46	0.87	0.54	0.89	2.3	0.38	0	0.1	0	0.33	0.82	0	2	3	3 / 18 (17%)	1 / 11 (9.1%)	2 / 7 (29%)	0.0909	0.286
Blautia_A	Blautia_A	0.074	0.93	1	-0.99	0.35	0.85	1	-0.5	NA	NA	NA	0.62	0.9	0.4	0.87	14	14	12	11	10	5.7	19	14	9.2	0.79	18 / 18 (100%)	11 / 11 (100%)	7 / 7 (100%)	1	1
CAG-103	CAG-103	0.25	0.93	1	-0.59	0.23	0.85	1	-0.63	0.33	1	1	0.22	0.81	0.25	0.83	0.68	0.26	0	0.19	0	0.4	0.38	0.45	0.37	1	7 / 18 (39%)	3 / 11 (27%)	4 / 7 (57%)	0.273	0.571
CAG-110	CAG-110	0.64	0.95	1	-0.28	0.97	0.97	1	0.021	1	1	1	0.72	0.92	0.63	0.91	0.92	0.15	0	0.057	0	0.13	0.31	0	0.81	2.4	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
CAG-1427	CAG-1427	0.65	0.95	1	-0.25	0.7	0.94	1	-0.2	1	1	1	0.65	0.91	0.55	0.9	0.47	0.11	0	0.074	0	0.17	0.15	0	0.35	1	4 / 18 (22%)	2 / 11 (18%)	2 / 7 (29%)	0.182	0.286
CAG-177	CAG-177	0.27	0.93	1	0.48	0.36	0.85	1	0.4	1	1	1	0.56	0.89	0.69	0.93	0.86	0.19	0	0.28	0	0.49	0.05	0	0.13	-2.5	4 / 18 (22%)	3 / 11 (27%)	1 / 7 (14%)	0.273	0.143
CAG-217	CAG-217	0.26	0.93	1	-0.65	0.33	0.85	1	-0.55	0.33	1	1	0.36	0.84	0.38	0.85	1.3	0.36	0	0.16	0	0.36	0.67	0	1	2.1	5 / 18 (28%)	2 / 11 (18%)	3 / 7 (43%)	0.182	0.429
CAG-274	CAG-274	0.7	0.95	1	0.2	0.41	0.87	1	0.41	0.6	1	1	0.39	0.84	0.47	0.87	0.62	0.17	0	0.17	0	0.3	0.17	0	0.46	0	5 / 18 (28%)	4 / 11 (36%)	1 / 7 (14%)	0.364	0.143
CAG-302	CAG-302	0.63	0.95	1	0.22	0.7	0.94	1	0.18	1	1	1	0.75	0.93	0.62	0.91	0.62	0.1	0	0.13	0	0.3	0.054	0	0.14	-1.3	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
CAG-41	CAG-41	0.73	0.95	1	0.2	0.33	0.85	1	0.52	0.33	1	1	0.32	0.83	0.47	0.88	0.81	0.5	0.42	0.44	0.48	0.35	0.58	0	1.1	0.4	11 / 18 (61%)	8 / 11 (73%)	3 / 7 (43%)	0.727	0.429
CAG-56	CAG-56	0.32	0.93	1	0.57	0.083	0.85	1	1	0.049	1	1	0.071	0.8	0.22	0.83	0.88	0.54	0.38	0.56	0.48	0.44	0.5	0	0.91	-0.16	11 / 18 (61%)	9 / 11 (82%)	2 / 7 (29%)	0.818	0.286
CAG-83	CAG-83	0.88	0.95	1	-0.084	0.84	0.94	1	0.097	1	1	1	0.73	0.92	0.63	0.92	1.3	0.22	0	0.17	0	0.37	0.32	0	0.83	0.91	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Clostridium	Clostridium	0.86	0.95	1	0.083	0.88	0.94	1	0.07	1	1	1	0.75	0.93	0.68	0.93	0.31	0.087	0	0.095	0	0.18	0.074	0	0.16	-0.36	5 / 18 (28%)	3 / 11 (27%)	2 / 7 (29%)	0.273	0.286
Collinsella	Collinsella	0.87	0.95	1	0.089	0.37	0.85	1	0.48	0.33	1	1	0.33	0.83	0.47	0.88	1.5	0.93	0.43	0.83	0.44	0.81	1.1	0	1.4	0.41	11 / 18 (61%)	8 / 11 (73%)	3 / 7 (43%)	0.727	0.429
Coprococcus	Coprococcus	0.41	0.95	1	-0.41	0.28	0.85	1	-0.55	0.33	1	1	0.24	0.82	0.4	0.87	2.4	0.93	0	0.79	0	1.4	1.2	0.9	1.3	0.6	7 / 18 (39%)	3 / 11 (27%)	4 / 7 (57%)	0.273	0.571
Coprococcus_A	Coprococcus_A	0.71	0.95	1	-0.19	0.66	0.94	1	-0.22	1	1	1	0.58	0.89	0.5	0.89	0.47	0.1	0	0.091	0	0.22	0.13	0	0.25	0.51	4 / 18 (22%)	2 / 11 (18%)	2 / 7 (29%)	0.182	0.286
Coprococcus_B	Coprococcus_B	0.82	0.95	1	0.12	0.59	0.94	1	0.28	0.63	1	1	0.59	0.9	0.85	0.96	0.68	0.46	0.5	0.45	0.48	0.36	0.47	0.56	0.55	0.063	12 / 18 (67%)	8 / 11 (73%)	4 / 7 (57%)	0.727	0.571
Dialister	Dialister	0.83	0.95	1	-0.11	0.86	0.94	1	-0.088	1	1	1	0.85	0.95	0.78	0.95	1.3	0.51	0	0.48	0	0.83	0.57	0	1	0.25	7 / 18 (39%)	4 / 11 (36%)	3 / 7 (43%)	0.364	0.429
Dorea	Dorea	0.87	0.95	1	-0.094	0.45	0.91	1	0.49	0.39	1	1	0.38	0.85	0.88	0.97	1.3	1.2	1.1	1.1	1	0.75	1.5	1.4	1.3	0.45	17 / 18 (94%)	11 / 11 (100%)	6 / 7 (86%)	1	0.857
ER4	ER4	0.47	0.95	1	-0.39	0.34	0.85	1	-0.51	0.53	1	1	0.34	0.84	0.34	0.83	0.36	0.06	0	0.044	0	0.14	0.086	0	0.16	0.97	3 / 18 (17%)	1 / 11 (9.1%)	2 / 7 (29%)	0.0909	0.286
Erysipelatoclostridium	Erysipelatoclostridium	0.83	0.95	1	-0.12	0.94	0.97	1	0.037	1	1	1	0.85	0.95	0.83	0.96	0.82	0.59	0.39	0.51	0.46	0.47	0.72	0.25	0.99	0.5	13 / 18 (72%)	8 / 11 (73%)	5 / 7 (71%)	0.727	0.714
Eubacterium_E	Eubacterium_E	0.72	0.95	1	0.18	0.7	0.94	1	0.2	1	1	1	0.7	0.92	0.9	0.97	2.2	1.9	1.8	2	2.1	1.2	1.8	1.7	1.2	-0.15	16 / 18 (89%)	10 / 11 (91%)	6 / 7 (86%)	0.909	0.857
Eubacterium_F	Eubacterium_F	0.67	0.95	1	-0.25	0.96	0.97	1	0.03	1	1	1	0.79	0.93	0.67	0.92	1.4	0.24	0	0.1	0	0.26	0.45	0	1.2	2.2	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Eubacterium_I	Eubacterium_I	0.63	0.95	1	-0.25	0.72	0.94	1	-0.19	1	1	1	0.73	0.92	0.7	0.93	0.63	0.14	0	0.11	0	0.25	0.19	0	0.36	0.79	4 / 18 (22%)	2 / 11 (18%)	2 / 7 (29%)	0.182	0.286
Eubacterium_R	Eubacterium_R	0.92	0.95	1	-0.051	0.83	0.94	1	0.1	1	1	1	0.76	0.93	0.66	0.93	1.5	0.25	0	0.2	0	0.46	0.33	0	0.86	0.72	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Faecalibacterium	Faecalibacterium	0.56	0.95	1	0.28	0.59	0.94	1	0.28	NA	NA	NA	0.65	0.92	0.86	0.97	6.5	6.5	5.7	7	6.3	4.8	5.6	5.2	3.8	-0.32	18 / 18 (100%)	11 / 11 (100%)	7 / 7 (100%)	1	1
Faecalicatena	Faecalicatena	0.068	0.93	1	-1.2	0.15	0.85	1	-0.78	0.33	1	1	0.2	0.81	0.14	0.8	1.3	0.65	0.1	0.22	0	0.32	1.3	1.6	1.2	2.6	9 / 18 (50%)	4 / 11 (36%)	5 / 7 (71%)	0.364	0.714
Fusicatenibacter	Fusicatenibacter	0.99	0.99	1	0.0072	0.72	0.94	1	0.19	1	1	1	0.7	0.92	0.62	0.92	4.9	4.3	3.2	4.1	3	3.2	4.7	3.8	5	0.2	16 / 18 (89%)	10 / 11 (91%)	6 / 7 (86%)	0.909	0.857
GCA-900066135	GCA-900066135	0.64	0.95	1	0.24	0.49	0.94	1	0.34	0.64	1	1	0.5	0.88	0.65	0.92	0.27	0.1	0	0.11	0	0.15	0.092	0	0.18	-0.26	7 / 18 (39%)	5 / 11 (45%)	2 / 7 (29%)	0.455	0.286
Gemmiger	Gemmiger	0.69	0.95	1	-0.23	0.84	0.94	1	0.11	1	1	1	0.78	0.94	0.77	0.95	2.9	2.6	2	2.1	1.7	1.6	3.3	2.2	4.1	0.65	16 / 18 (89%)	10 / 11 (91%)	6 / 7 (86%)	0.909	0.857
Holdemanella	Holdemanella	0.32	0.93	1	-0.6	0.35	0.85	1	-0.52	0.53	1	1	0.35	0.84	0.36	0.85	2.6	0.43	0	0.16	0	0.55	0.84	0	1.5	2.4	3 / 18 (17%)	1 / 11 (9.1%)	2 / 7 (29%)	0.0909	0.286
Intestinibacter	Intestinibacter	0.91	0.95	1	-0.055	0.8	0.94	1	-0.13	1	1	1	0.64	0.9	0.56	0.9	0.26	0.057	0	0.061	0	0.14	0.051	0	0.098	-0.26	4 / 18 (22%)	2 / 11 (18%)	2 / 7 (29%)	0.182	0.286
KLE1615	KLE1615	0.18	0.93	1	0.66	0.075	0.85	1	0.86	0.15	1	1	0.12	0.8	0.23	0.81	1.3	0.52	0	0.67	0.22	0.81	0.28	0	0.73	-1.3	7 / 18 (39%)	6 / 11 (55%)	1 / 7 (14%)	0.545	0.143
Lachnospira	Lachnospira	0.75	0.95	1	-0.16	0.82	0.94	1	-0.12	1	1	1	0.74	0.93	0.65	0.93	1.3	0.5	0	0.45	0	0.77	0.58	0	0.89	0.37	7 / 18 (39%)	4 / 11 (36%)	3 / 7 (43%)	0.364	0.429
Lactobacillus_B	Lactobacillus_B	0.84	0.95	1	-0.11	0.89	0.94	1	0.072	1	1	1	0.77	0.93	0.68	0.93	1.6	0.26	0	0.18	0	0.44	0.38	0	1	1.1	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Oscillibacter	Oscillibacter	0.85	0.95	1	-0.1	0.89	0.94	1	0.076	1	1	1	0.74	0.93	0.62	0.91	0.71	0.12	0	0.084	0	0.19	0.17	0	0.46	1	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Parabacteroides	Parabacteroides	0.93	0.95	1	0.037	0.5	0.94	1	-0.32	0.53	1	1	0.39	0.85	0.35	0.83	0.61	0.1	0	0.14	0	0.47	0.037	0	0.062	-1.9	3 / 18 (17%)	1 / 11 (9.1%)	2 / 7 (29%)	0.0909	0.286
Phascolarctobacterium	Phascolarctobacterium	0.76	0.95	1	0.13	0.84	0.94	1	-0.09	1	1	1	0.6	0.89	0.48	0.89	0.71	0.16	0	0.22	0	0.64	0.06	0	0.1	-1.9	4 / 18 (22%)	2 / 11 (18%)	2 / 7 (29%)	0.182	0.286
Prevotella	Prevotella	0.27	0.93	1	0.45	0.56	0.94	1	0.26	1	1	1	0.71	0.92	0.66	0.92	5.9	0.98	0	1.6	0	3.5	0.074	0	0.2	-4.4	3 / 18 (17%)	2 / 11 (18%)	1 / 7 (14%)	0.182	0.143
Romboutsia	Romboutsia	0.43	0.95	1	0.36	0.54	0.94	1	0.27	1	1	1	0.67	0.91	0.76	0.94	0.64	0.21	0	0.28	0	0.42	0.11	0	0.21	-1.3	6 / 18 (33%)	4 / 11 (36%)	2 / 7 (29%)	0.364	0.286
Roseburia	Roseburia	0.33	0.93	1	-0.58	0.37	0.85	1	-0.5	0.53	1	1	0.38	0.85	0.44	0.88	0.57	0.095	0	0.04	0	0.13	0.18	0	0.32	2.2	3 / 18 (17%)	1 / 11 (9.1%)	2 / 7 (29%)	0.0909	0.286
Ruminiclostridium_C	Ruminiclostridium_C	0.3	0.93	1	-0.6	0.3	0.85	1	-0.56	0.33	1	1	0.29	0.83	0.33	0.84	0.23	0.064	0	0.032	0	0.073	0.11	0	0.18	1.8	5 / 18 (28%)	2 / 11 (18%)	3 / 7 (43%)	0.182	0.429
Ruminococcus_A	Ruminococcus_A	0.87	0.95	1	-0.079	0.58	0.94	1	-0.27	0.63	1	1	0.45	0.86	0.54	0.9	0.97	0.43	0	0.47	0	0.81	0.37	0.16	0.48	-0.35	8 / 18 (44%)	4 / 11 (36%)	4 / 7 (57%)	0.364	0.571
Ruminococcus_C	Ruminococcus_C	0.74	0.95	1	0.16	0.81	0.94	1	0.12	1	1	1	0.81	0.94	0.79	0.95	1	0.46	0	0.51	0	0.6	0.38	0	0.53	-0.42	8 / 18 (44%)	5 / 11 (45%)	3 / 7 (43%)	0.455	0.429
Ruminococcus_D	Ruminococcus_D	0.12	0.93	1	0.69	0.25	0.85	1	0.57	0.37	1	1	0.28	0.82	0.34	0.86	3.6	1.6	0	2.3	0.82	3.2	0.48	0	0.93	-2.3	8 / 18 (44%)	6 / 11 (55%)	2 / 7 (29%)	0.545	0.286
Ruminococcus_E	Ruminococcus_E	0.2	0.93	1	0.71	0.053	0.85	1	1.2	0.047	1	1	0.056	0.8	0.065	0.79	4.4	3.2	2.8	3.7	3	3.3	2.3	0	3.5	-0.69	13 / 18 (72%)	10 / 11 (91%)	3 / 7 (43%)	0.909	0.429
Streptococcus	Streptococcus	0.33	0.93	1	-0.48	0.33	0.85	1	-0.48	0.37	1	1	0.37	0.84	0.36	0.86	0.92	0.51	0.35	0.42	0	0.7	0.65	0.66	0.66	0.63	10 / 18 (56%)	5 / 11 (45%)	5 / 7 (71%)	0.455	0.714
TF01-11	TF01-11	0.38	0.95	1	-0.44	0.19	0.85	1	-0.7	0.25	1	1	0.18	0.81	0.19	0.79	0.43	0.095	0	0.084	0	0.28	0.11	0	0.17	0.39	4 / 18 (22%)	1 / 11 (9.1%)	3 / 7 (43%)	0.0909	0.429
UBA11774	UBA11774	0.6	0.95	1	-0.27	0.54	0.94	1	-0.31	0.63	1	1	0.46	0.87	0.46	0.88	0.96	0.32	0	0.27	0	0.6	0.4	0	0.68	0.57	6 / 18 (33%)	3 / 11 (27%)	3 / 7 (43%)	0.273	0.429
UBA7160	UBA7160	0.9	0.95	1	-0.074	0.62	0.94	1	0.24	1	1	1	0.63	0.9	0.66	0.92	0.54	0.12	0	0.077	0	0.15	0.19	0	0.5	1.3	4 / 18 (22%)	3 / 11 (27%)	1 / 7 (14%)	0.273	0.143

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Methods:

P Fisher's exact test: differences in detection rate were detected by Fisher's exact test.

P Welch's t-test (sqrt): Differentially abundant species were identified by Welch's t-test.

P Welch's t-test (clr): Differentially abundant species were identified by Welch's t-test.

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.