philippmuench/aih_metagenome

code to reproduce AIH results

AIH analysis

notes

code depends on metagenomeSeq and other libraries that must be installed via either Bioconductor or CRAN. Some libraries that were used in this analysis were removed from CRAN e.g. ('biom'). You may need install these libraries (e.g. using devtools::install_github) manually to run these scripts.

data

data which will be used by the scripts is located in the data/ folder

figure 1

figure 1a

alpha diversity

soource('figure_1a.R')

script generates

• results/figure_1a_class.pdf

which was modified manually (using pvalues from supplementary table 2) to create part a of ms/version_september_17/figure1.pdf

figure 1b

triplot

soource('figure_1b.R')

script generates

• results/figure_1b_triplot.pdf

which was modified to create part b of ms/version_september_17/figure1.pdf

figure 1c

alpha diversity

soource('figure_1c.R')

script generates

• results/figure_1c_chao1.pdf
• test statistics gets printed to screen:

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = value ~ type, data = df.adiv)

$type
                     diff       lwr        upr     p adj
control-AIH    -0.2994906 -1.252769 0.65378825 0.7308472
others-AIH     -0.8918631 -1.806463 0.02273673 0.0574292
others-control -0.5923725 -1.463349 0.27860441 0.2384276

which was modified manually to create part c of ms/version_september_17/figure1.pdf

figure 2

figure 2a

PCOA

soource('figure_2a.R')

script generates

• results/figure_2a_print.pdf
• results/figure_2a_label.pdf

which was modified manually to create part a of ms/version_september_17/figure2.pdf

figure 2b

PCOA contrained by cohort

soource('figure_2b.R')

script generates

• results/figure_2b_constrained_by_cohort_print.pdf
• results/figure_2b_constrained_by_cohort_label.pdf

which was modified manually to create part b of ms/version_september_17/figure2.pdf

figure 2c

PCOA contrained by cohort

soource('figure_2c.R')

script generates

• results/figure_2b_constrained_by_liver_print.pdf
• results/figure_2b_constrained_by_liver.pdf
• results/figure_2b_constrained_by_liver_label.pdf

which was modified manually to create part c of ms/version_september_17/figure2.pdf

figure 3

analysis on OTU level

soource('figure_3.R')

script generates

• results/figure_3_triplot.pdf
• results/figure_3_aih_db.csv
• results/figure_3_control_db.csv
• results/figure_3_healthy_db.csv

which was modified manually to create ms/version_september_17/figure3.pdf

supplementary figure 1

soource('figure_s1.R')

script generates

• results/figure_s1a_observed.pdf
• results/figure_s1b_shannon.pdf

which was modified manually to create part c of ms/version_september_17/figure_s3.pdf

supplementary figure 2

soource('figure_s2.R')

script generates

• results/figure_s2.pdf

which was modified manually to create part c of ms/version_september_17/figure_s2.pdf

supplementary figure 3

soource('figure_s3.R')

script generates

• results/figure_s3.pdf

which was modified manually to create part c of ms/version_september_17/figure_s3.pdf

unsorted analysis

correlation of alpha diversity with hep. status

• figure 5, no groups
• figure 5, dataset

statistical significance between groups: P = 0.00311

            Df  Sum Sq Mean Sq F value  Pr(>F)   
marker       3  920347  306782   5.212 0.00311 **
Residuals   54 3178690   58865                   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

detailed statistics:

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = chao1 ~ marker, data = alpha)

$marker
                                                   diff       lwr       upr     p adj
keine_hepatopathie-hepatop_ohne_veraenderung  152.38325 -146.9897 451.75620 0.5361788
mit_fibrose-hepatop_ohne_veraenderung         -67.77229 -394.1865 258.64188 0.9460486
mit_zirrhose-hepatop_ohne_veraenderung       -140.15217 -437.8757 157.57134 0.5995773
mit_fibrose-keine_hepatopathie               -220.15553 -461.5826  21.27157 0.0858399
mit_zirrhose-keine_hepatopathie              -292.53541 -493.4835 -91.58736 0.0016946
mit_zirrhose-mit_fibrose                      -72.37988 -311.7586 166.99883 0.8533967

correlation of alpha diversity with markers

• figure 6
• figure 6 (with mean line)

correlation coefficients will be printed to screen (for chao1, shannon, observed)

shannon

> printCorrelationCoef(chao1)
control

	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "others"), ]$adiv and df.adiv[which(df.adiv$type == "others"), ]$ifap
t = -1.2159, df = 19, p-value = 0.2389
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.6275839  0.1843826
sample estimates:
       cor 
-0.2686908 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "others"), ]$adiv and df.adiv[which(df.adiv$type == "others"), ]$lbp
t = 0.47462, df = 19, p-value = 0.6405
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.3392953  0.5158291
sample estimates:
      cor 
0.1082462 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "others"), ]$adiv and df.adiv[which(df.adiv$type == "others"), ]$sCD14
t = -0.96352, df = 19, p-value = 0.3474
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.5923340  0.2380273
sample estimates:
       cor 
-0.2158375 

healthy

	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "control"), ]$adiv and df.adiv[which(df.adiv$type == "control"), ]$ifap
t = -0.21226, df = 10, p-value = 0.8362
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.6171537  0.5271918
sample estimates:
        cor 
-0.06697288 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "control"), ]$adiv and df.adiv[which(df.adiv$type == "control"), ]$lbp
t = -0.72758, df = 10, p-value = 0.4836
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.7071303  0.4013207
sample estimates:
       cor 
-0.2242239 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "control"), ]$adiv and df.adiv[which(df.adiv$type == "control"), ]$sCD14
t = -0.14956, df = 9, p-value = 0.8844
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.6308246  0.5670197
sample estimates:
        cor 
-0.04979144 

AIH

	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH"), ]$adiv and df.adiv[which(df.adiv$type == "AIH"), ]$ifap
t = 0.58046, df = 14, p-value = 0.5708
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.3705645  0.6031700
sample estimates:
      cor 
0.1533008 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH"), ]$adiv and df.adiv[which(df.adiv$type == "AIH"), ]$lbp
t = 0.70243, df = 14, p-value = 0.4939
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.3425250  0.6232134
sample estimates:
      cor 
0.1845082 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH"), ]$adiv and df.adiv[which(df.adiv$type == "AIH"), ]$sCD14
t = -2.4767, df = 14, p-value = 0.02664
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.82259702 -0.07744908
sample estimates:
       cor 
-0.5519635 

all

	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |  and df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |     df.adiv$type == "others"), ]$adiv and     df.adiv$type == "others"), ]$ifap
t = -2.2723, df = 47, p-value = 0.02769
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.54738273 -0.03665839
sample estimates:
       cor 
-0.3146119 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |  and df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |     df.adiv$type == "others"), ]$adiv and     df.adiv$type == "others"), ]$lbp
t = -0.54859, df = 47, p-value = 0.5859
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.3530432  0.2060530
sample estimates:
        cor 
-0.07976532 


	Pearson's product-moment correlation

data:  df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |  and df.adiv[which(df.adiv$type == "AIH" | df.adiv$type == "control" |     df.adiv$type == "others"), ]$adiv and     df.adiv$type == "others"), ]$sCD14
t = -3.8275, df = 46, p-value = 0.0003892
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.6805680 -0.2409882
sample estimates:
       cor 
-0.4914704 

supplementary table 2

statistics on class level

soource('table_s2.R')

script generates

• results/table_s2_class_aih_vs_control.tsv
• table_s2_class_aih_vs_helathy.tsv
• table_s2_class_healthy_vs_control.tsv

which was modified manually to create ms/version_september_17/Table_S2.xlsx

healthy vs. non-AIH hep. control

Class*	logFC	t	P value	FDR	B	sig. Level
RF3	1.47	3.45	0.003716	0.027254	-1.92	*
Opitutae	1.18	1.96	0.083799	0.307263	-4.45	n.s.
Deferribacteres	1.03	1.55	0.142350	0.377765	-4.80	n.s.
[Lentisphaeria]	0.72	0.87	0.402788	0.579287	-5.98	n.s.
Erysipelotrichi	0.37	1.10	0.277168	0.435550	-6.44	n.s.
Clostridia	0.33	2.32	0.024737	0.136056	-4.48	n.s.
4C0d-2	0.15	0.30	0.769840	0.865654	-6.62	n.s.
Mollicutes	0.11	0.13	0.899250	0.905493	-6.62	n.s.
Deltaproteobacteria	-0.05	-0.12	0.905493	0.905493	-6.85	n.s.
Bacilli	-0.09	-0.27	0.786958	0.865654	-7.03	n.s.
Bacteroidia	-0.11	-0.57	0.572722	0.699994	-6.90	n.s.
Alphaproteobacteria	-0.18	-0.81	0.421300	0.579287	-6.73	n.s.
Betaproteobacteria	-0.25	-1.10	0.276335	0.435550	-6.44	n.s.
Verrucomicrobiae	-0.36	-0.60	0.554026	0.699994	-6.71	n.s.
Coriobacteriia	-0.43	-1.29	0.204429	0.408857	-6.20	n.s.
Flavobacteriia	-0.49	-1.17	0.257856	0.435550	-5.86	n.s.
Chloroplast	-0.50	-1.42	0.166344	0.377765	-5.76	n.s.
Actinobacteria	-0.62	-1.45	0.154523	0.377765	-6.02	n.s.
Epsilonproteobacteria	-0.93	-1.42	0.171711	0.377765	-5.54	n.s.
Gammaproteobacteria	-1.38	-4.05	0.000203	0.002229	0.01	* *
Deinococci	-1.87	-2.07	0.073636	0.307263	-4.22	n.s.
Fusobacteriia	-2.33	-6.53	0.000001	0.000022	5.67	* * *

AIH vs. healthy

Class*	logFC	t	P value	FDR	B	sig. Level
Fusobacteriia	1.67	3.39	0.0027	0.0314	-1.57	*
Gammaproteobacteria	1.51	4.28	0.0001	0.0027	1.04	* *
Synergistia	0.76	0.81	0.4371	0.7733	-5.16	n.s.
Verrucomicrobiae	0.44	0.83	0.4101	0.7733	-6.00	n.s.
Actinobacteria	0.41	1.08	0.2876	0.7158	-5.87	n.s.
Bacteroidia	0.29	1.39	0.1728	0.6025	-5.50	n.s.
Coriobacteriia	0.29	1.03	0.3112	0.7158	-5.91	n.s.
Betaproteobacteria	0.24	0.94	0.3523	0.7365	-5.99	n.s.
Erysipelotrichi	0.23	0.72	0.4743	0.7791	-6.18	n.s.
RF3	0.21	0.41	0.6899	0.8755	-5.71	n.s.
Bacilli	0.16	0.56	0.5804	0.8343	-6.29	n.s.
Deferribacteres	0.14	0.28	0.7846	0.8755	-5.90	n.s.
4C0d-2	0.13	0.26	0.7980	0.8755	-6.06	n.s.
Deinococci	0.11	0.15	0.8809	0.9210	-5.61	n.s.
Chloroplast	0.11	0.26	0.7993	0.8755	-6.17	n.s.
Epsilonproteobacteria	0.05	0.08	0.9404	0.9404	-5.98	n.s.
Clostridia	-0.25	-1.32	0.1937	0.6025	-5.59	n.s.
Flavobacteriia	-0.25	-0.57	0.5737	0.8343	-5.86	n.s.
Mollicutes	-0.28	-0.38	0.7050	0.8755	-6.12	n.s.
Alphaproteobacteria	-0.37	-1.56	0.1264	0.5814	-5.26	n.s.
Deltaproteobacteria	-0.45	-1.28	0.2096	0.6025	-5.55	n.s.
[Lentisphaeria]	-1.27	-1.83	0.0861	0.4953	-4.37	n.s.
Opitutae	-1.52	-1.99	0.0719	0.4953	-4.05	n.s.

AIH vs. non-AIH hep. control

Class*	logFC	t	P value	FDR	B	sig. Level
RF3	1.68	2.34	0.04	0.51	-4.57	n.s.
Deferribacteres	1.17	0.85	0.42	0.84	-4.60	n.s.
Erysipelotrichi	0.60	1.54	0.13	0.63	-4.54	n.s.
4C0d-2	0.28	0.36	0.72	0.92	-4.61	n.s.
Bacteroidia	0.18	0.93	0.36	0.84	-4.60	n.s.
Gammaproteobacteria	0.14	0.37	0.71	0.92	-4.63	n.s.
Clostridia	0.08	0.48	0.64	0.92	-4.63	n.s.
Verrucomicrobiae	0.07	0.10	0.92	0.96	-4.63	n.s.
Bacilli	0.07	0.17	0.86	0.94	-4.64	n.s.
Betaproteobacteria	0.00	-0.02	0.98	0.98	-4.64	n.s.
Coriobacteriia	-0.14	-0.44	0.66	0.92	-4.63	n.s.
Mollicutes	-0.17	-0.18	0.86	0.94	-4.61	n.s.
Actinobacteria	-0.21	-0.53	0.60	0.92	-4.63	n.s.
Elusimicrobia	-0.28	-0.19	0.86	0.94	-4.60	n.s.
Opitutae	-0.34	-0.47	0.65	0.92	-4.60	n.s.
Chloroplast	-0.39	-0.76	0.45	0.84	-4.61	n.s.
Deltaproteobacteria	-0.50	-1.07	0.30	0.84	-4.59	n.s.
[Lentisphaeria]	-0.56	-0.79	0.44	0.84	-4.60	n.s.
Alphaproteobacteria	-0.56	-2.17	0.04	0.51	-4.45	n.s.
TM7-3	-0.58	-0.85	0.42	0.84	-4.60	n.s.
Fusobacteriia	-0.66	-1.29	0.21	0.72	-4.58	n.s.
Flavobacteriia	-0.74	-1.48	0.16	0.64	-4.58	n.s.
Epsilonproteobacteria	-0.88	-1.69	0.10	0.63	-4.55	n.s.
Deinococci	-1.76	-1.69	0.13	0.63	-4.59	n.s.

supplementary table 3

statistics on family level

soource('table_s3.R')

script generates

• results/table_s3_family_aih_vs_control.tsv
• table_s3_family_aih_vs_helathy.tsv
• table_s3_family_healthy_vs_control.tsv

which was modified manually to create ms/version_september_17/Table_S3.xlsx

healthy vs. non-AIH hep. control

Family*	logFC	t	P value	FDR	B	sig. Level
Fusobacteriaceae	-2.23	-5.37	0.00001	0.0004	3.65	* * *
Prevotellaceae	-1.89	-3.16	0.00265	0.0212	-2.31	*
Deinococcaceae	-1.87	-1.81	0.09122	0.2128	-4.44	n.s.
Veillonellaceae	-1.79	-4.70	0.00002	0.0005	2.35	* * *
Enterococcaceae	-1.65	-2.98	0.00647	0.0362	-2.57	*
Enterobacteriaceae	-1.64	-3.45	0.00122	0.0114	-1.52	*
Pasteurellaceae	-1.52	-3.70	0.00065	0.0090	-0.82	* *
Leuconostocaceae	-1.49	-1.64	0.12009	0.2495	-4.71	n.s.
Micrococcaceae	-1.47	-2.39	0.02366	0.0780	-3.90	n.s.
Staphylococcaceae	-1.41	-2.61	0.01496	0.0573	-3.35	n.s.
Streptococcaceae	-1.36	-3.11	0.00311	0.0218	-2.46	*
Campylobacteraceae	-1.34	-1.79	0.08719	0.2123	-4.78	n.s.
Gemellaceae	-1.30	-2.28	0.03212	0.0947	-4.03	n.s.
[Paraprevotellaceae]	-1.28	-2.67	0.01156	0.0498	-3.41	*
Carnobacteriaceae	-1.21	-3.48	0.00119	0.0114	-1.44	*
Moraxellaceae	-1.13	-2.29	0.02858	0.0889	-4.18	n.s.
[Weeksellaceae]	-1.03	-1.49	0.15262	0.2849	-5.16	n.s.
Rhodobacteraceae	-0.93	-1.16	0.25988	0.4158	-5.61	n.s.
Corynebacteriaceae	-0.87	-1.66	0.10904	0.2442	-5.15	n.s.
Sphingomonadaceae	-0.76	-2.51	0.01535	0.0573	-3.93	n.s.
Eubacteriaceae	-0.73	-1.21	0.24008	0.3954	-5.57	n.s.
Actinomycetaceae	-0.70	-1.76	0.08416	0.2123	-5.35	n.s.
Comamonadaceae	-0.66	-2.16	0.03542	0.0992	-4.62	n.s.
Peptococcaceae	-0.61	-1.33	0.19561	0.3423	-5.56	n.s.
Lactobacillaceae	-0.43	-0.90	0.37561	0.5535	-6.41	n.s.
Coriobacteriaceae	-0.43	-1.25	0.21907	0.3717	-6.13	n.s.
Verrucomicrobiaceae	-0.36	-0.62	0.53792	0.6148	-6.57	n.s.
Bifidobacteriaceae	-0.36	-0.72	0.47494	0.5811	-6.66	n.s.
Caulobacteraceae	-0.32	-0.69	0.49812	0.5811	-6.38	n.s.
Methylobacteriaceae	-0.31	-0.36	0.72166	0.7924	-6.06	n.s.
Pseudomonadaceae	-0.29	-0.69	0.49613	0.5811	-6.46	n.s.
Peptostreptococcaceae	-0.24	-0.42	0.67333	0.7541	-6.69	n.s.
Alcaligenaceae	-0.23	-0.69	0.49373	0.5811	-6.62	n.s.
Desulfovibrionaceae	-0.08	-0.19	0.84964	0.8811	-6.71	n.s.
Oxalobacteraceae	-0.02	-0.05	0.96040	0.9604	-6.91	n.s.
Neisseriaceae	0.04	0.05	0.95947	0.9604	-6.15	n.s.
[Tissierellaceae]	0.12	0.25	0.80721	0.8529	-6.54	n.s.
[Odoribacteraceae]	0.13	0.30	0.76323	0.8219	-6.80	n.s.
[Mogibacteriaceae]	0.23	0.75	0.45851	0.5811	-6.62	n.s.
Bacteroidaceae	0.26	0.69	0.49086	0.5811	-6.69	n.s.
Clostridiaceae	0.30	0.80	0.42928	0.5811	-6.60	n.s.
Erysipelotrichaceae	0.37	1.07	0.29030	0.4394	-6.34	n.s.
Dehalobacteriaceae	0.50	0.77	0.44726	0.5811	-6.13	n.s.
Bradyrhizobiaceae	0.53	0.81	0.42790	0.5811	-5.96	n.s.
Porphyromonadaceae	0.62	1.58	0.12030	0.2495	-5.60	n.s.
Victivallaceae	0.72	0.88	0.39199	0.5629	-5.86	n.s.
Lachnospiraceae	0.75	2.69	0.00958	0.0483	-3.51	*
Ruminococcaceae	0.80	2.66	0.01036	0.0483	-3.58	*
S24-7	0.84	1.56	0.12653	0.2531	-5.58	n.s.
Turicibacteraceae	0.88	1.48	0.14561	0.2812	-5.67	n.s.
Deferribacteraceae	1.03	1.11	0.27826	0.4328	-5.20	n.s.
Rikenellaceae	1.12	2.09	0.04174	0.1113	-4.81	n.s.
Christensenellaceae	1.14	2.50	0.01643	0.0575	-3.89	n.s.
[Cerasicoccaceae]	1.18	1.42	0.17454	0.3153	-5.05	n.s.
[Barnesiellaceae]	1.46	3.02	0.00395	0.0246	-2.68	*
no match	1.96	4.38	0.00006	0.0011	1.28	* *

AIH vs. healthy

Family*	logFC	t	P value	FDR	B	sig. Level
Succinivibrionaceae	1.98	1.02	0.33	0.62	-4.75	n.a.
Prevotellaceae	1.95	3.38	0.00	0.07	-1.19	n.a.
Pasteurellaceae	1.53	3.25	0.00	0.07	-1.57	n.a.
Dehalobacteriaceae	1.30	2.10	0.05	0.34	-3.80	n.a.
Fusobacteriaceae	1.25	2.53	0.02	0.25	-3.11	n.a.
Veillonellaceae	1.08	2.90	0.01	0.10	-2.35	n.a.
Peptococcaceae	0.79	1.58	0.13	0.49	-4.48	n.a.
Streptococcaceae	0.77	2.07	0.05	0.34	-4.07	n.a.
Micrococcaceae	0.64	1.09	0.29	0.62	-5.11	n.a.
Staphylococcaceae	0.63	1.60	0.12	0.49	-4.55	n.a.
Moraxellaceae	0.63	1.62	0.12	0.49	-4.61	n.a.
Pseudomonadaceae	0.59	1.37	0.18	0.50	-4.95	n.a.
Carnobacteriaceae	0.56	1.47	0.15	0.50	-4.92	n.a.
Campylobacteraceae	0.54	0.69	0.50	0.75	-5.25	n.a.
[Paraprevotellaceae]	0.51	0.95	0.35	0.62	-5.45	n.a.
Comamonadaceae	0.50	1.31	0.20	0.50	-5.17	n.a.
Caulobacteraceae	0.46	0.95	0.35	0.62	-5.33	n.a.
Enterobacteriaceae	0.44	0.94	0.36	0.62	-5.50	n.a.
Verrucomicrobiaceae	0.44	0.83	0.41	0.67	-5.60	n.a.
Sphingomonadaceae	0.41	1.29	0.20	0.50	-5.22	n.a.
Peptostreptococcaceae	0.37	0.66	0.51	0.75	-5.67	n.a.
Actinomycetaceae	0.36	1.11	0.27	0.62	-5.42	n.a.
[Weeksellaceae]	0.35	0.59	0.56	0.75	-5.35	n.a.
Gemellaceae	0.30	0.62	0.54	0.75	-5.40	n.a.
Bifidobacteriaceae	0.30	0.63	0.53	0.75	-5.81	n.a.
Coriobacteriaceae	0.29	1.00	0.33	0.62	-5.54	n.a.
[Odoribacteraceae]	0.23	0.51	0.61	0.75	-5.89	n.a.
Lactobacillaceae	0.23	0.50	0.62	0.75	-5.84	n.a.
Erysipelotrichaceae	0.23	0.71	0.48	0.75	-5.78	n.a.
Eubacteriaceae	0.18	0.39	0.70	0.79	-5.51	n.a.
Deferribacteraceae	0.14	0.27	0.79	0.86	-5.51	n.a.
Oxalobacteraceae	0.12	0.34	0.73	0.81	-5.93	n.a.
Bacteroidaceae	0.03	0.10	0.92	0.97	-6.02	n.a.
Alcaligenaceae	0.02	0.05	0.96	1.00	-6.00	n.a.
Clostridiaceae	0.00	0.00	1.00	1.00	-6.03	n.a.
Corynebacteriaceae	-0.01	-0.01	0.99	1.00	-5.59	n.a.
Desulfovibrionaceae	-0.16	-0.43	0.67	0.78	-5.80	n.a.
Christensenellaceae	-0.20	-0.52	0.61	0.75	-5.81	n.a.
Rikenellaceae	-0.26	-0.56	0.58	0.75	-5.87	n.a.
Porphyromonadaceae	-0.32	-0.96	0.34	0.62	-5.54	n.a.
Turicibacteraceae	-0.33	-0.55	0.59	0.75	-5.79	n.a.
[Mogibacteriaceae]	-0.35	-1.10	0.28	0.62	-5.42	n.a.
Ruminococcaceae	-0.37	-1.58	0.12	0.49	-4.85	n.a.
Lachnospiraceae	-0.39	-1.84	0.07	0.48	-4.46	n.a.
Rhodobacteraceae	-0.39	-0.46	0.65	0.77	-5.21	n.a.
Bradyrhizobiaceae	-0.55	-0.89	0.39	0.65	-5.14	n.a.
S24-7	-0.62	-1.36	0.18	0.50	-5.06	n.a.
[Barnesiellaceae]	-0.72	-1.29	0.20	0.50	-5.24	n.a.
[Tissierellaceae]	-0.94	-1.45	0.16	0.50	-4.64	n.a.
	-1.00	-2.25	0.03	0.31	-3.73	n.a.
Victivallaceae	-1.27	-1.79	0.09	0.48	-4.21	n.a.
[Cerasicoccaceae]	-1.52	-1.87	0.09	0.48	-4.08	n.a.

AIH vs. non-AIH hep. control

Family*	logFC	t	P value	FDR	B	sig. Level
Succinivibrionaceae	2.37	2.19	0.04	0.63	-4.57	n.s.
Dehalobacteriaceae	1.80	2.50	0.02	0.58	-4.56	n.s.
no match	0.96	1.92	0.06	0.63	-4.52	n.s.
Christensenellaceae	0.93	1.67	0.10	0.63	-4.56	n.s.
Rikenellaceae	0.85	1.34	0.19	0.63	-4.57	n.s.
[Barnesiellaceae]	0.74	1.22	0.23	0.63	-4.58	n.s.
Erysipelotrichaceae	0.60	1.50	0.14	0.63	-4.56	n.s.
Turicibacteraceae	0.55	0.75	0.46	0.79	-4.60	n.s.
Ruminococcaceae	0.43	1.22	0.23	0.63	-4.58	n.s.
[Odoribacteraceae]	0.36	0.74	0.46	0.79	-4.61	n.s.
Lachnospiraceae	0.36	1.14	0.26	0.63	-4.59	n.s.
Pseudomonadaceae	0.30	0.62	0.54	0.82	-4.61	n.s.
Porphyromonadaceae	0.30	0.66	0.51	0.81	-4.61	n.s.
Bacteroidaceae	0.30	0.71	0.48	0.79	-4.61	n.s.
Clostridiaceae	0.29	0.70	0.49	0.79	-4.61	n.s.
S24-7	0.22	0.40	0.69	0.90	-4.61	n.s.
Leptotrichiaceae	0.19	0.19	0.85	0.96	-4.60	n.s.
Aerococcaceae	0.18	0.16	0.87	0.96	-4.60	n.s.
Peptococcaceae	0.17	0.26	0.80	0.93	-4.60	n.s.
Caulobacteraceae	0.14	0.31	0.76	0.93	-4.61	n.s.
Peptostreptococcaceae	0.13	0.18	0.85	0.96	-4.61	n.s.
Oxalobacteraceae	0.10	0.28	0.78	0.93	-4.62	n.s.
Verrucomicrobiaceae	0.07	0.10	0.92	0.97	-4.61	n.s.
Prevotellaceae	0.06	0.08	0.94	0.97	-4.62	n.s.
Pasteurellaceae	0.01	0.03	0.98	0.98	-4.62	n.s.
Bradyrhizobiaceae	-0.02	-0.03	0.98	0.98	-4.61	n.s.
Bifidobacteriaceae	-0.06	-0.12	0.91	0.97	-4.62	n.s.
[Mogibacteriaceae]	-0.11	-0.31	0.76	0.93	-4.62	n.s.
Coriobacteriaceae	-0.14	-0.41	0.69	0.90	-4.62	n.s.
Comamonadaceae	-0.16	-0.46	0.65	0.89	-4.62	n.s.
Lactobacillaceae	-0.21	-0.38	0.71	0.90	-4.61	n.s.
Alcaligenaceae	-0.21	-0.58	0.57	0.84	-4.61	n.s.
Desulfovibrionaceae	-0.24	-0.51	0.61	0.87	-4.61	n.s.
Actinomycetaceae	-0.34	-0.85	0.40	0.79	-4.60	n.s.
Sphingomonadaceae	-0.35	-1.16	0.25	0.63	-4.59	n.s.
Neisseriaceae	-0.41	-0.51	0.61	0.87	-4.60	n.s.
Moraxellaceae	-0.50	-0.87	0.39	0.79	-4.60	n.s.
Eubacteriaceae	-0.55	-0.75	0.46	0.79	-4.60	n.s.
Victivallaceae	-0.56	-0.72	0.48	0.79	-4.60	n.s.
Streptococcaceae	-0.59	-1.17	0.25	0.63	-4.59	n.s.
Carnobacteriaceae	-0.64	-1.47	0.15	0.63	-4.57	n.s.
[Weeksellaceae]	-0.69	-0.92	0.37	0.78	-4.60	n.s.
Veillonellaceae	-0.71	-1.78	0.08	0.63	-4.54	n.s.
Enterococcaceae	-0.73	-1.01	0.32	0.71	-4.60	n.s.
[Paraprevotellaceae]	-0.77	-1.24	0.22	0.63	-4.58	n.s.
Staphylococcaceae	-0.78	-1.16	0.26	0.63	-4.59	n.s.
Campylobacteraceae	-0.80	-1.28	0.21	0.63	-4.59	n.s.
[Tissierellaceae]	-0.82	-1.32	0.20	0.63	-4.59	n.s.
Micrococcaceae	-0.83	-1.24	0.23	0.63	-4.59	n.s.
Corynebacteriaceae	-0.88	-1.29	0.21	0.63	-4.59	n.s.
Fusobacteriaceae	-0.99	-1.78	0.09	0.63	-4.57	n.s.
Gemellaceae	-1.00	-1.69	0.10	0.63	-4.58	n.s.
Enterobacteriaceae	-1.21	-2.40	0.02	0.58	-4.50	n.s.
Rhodobacteraceae	-1.32	-1.09	0.29	0.67	-4.59	n.s.
Deinococcaceae	-1.64	-1.26	0.23	0.63	-4.59	n.s.

supplementary table 4

statistics on genus level

soource('table_s4.R')

script generates

• results/table_s4_genus_aih_vs_control.tsv
• table_s3_genus_aih_vs_helathy.tsv
• table_s3_genus_healthy_vs_control.tsv

which was modified manually to create ms/version_september_17/Table_S4.xlsx

aih_metagenome's Issues

Are there phyla, classes, genera etc. that are associated with increasing disease status? Not sure if this can be sensibly done..

• for most probes there is no numeric scale on increasing disease status
• samples have been labeled by Goeser as 1,2,3 for increasing liver disease (not really great data for trend analysis, can look for differences between groups, and see if a differnce increases from healthy in comparison to second worst and healthy to worst group (which ones these are Dr. Goeser knows).

Correct falsely labeled sample, rerun analysed relatred to liver status

-has chao1 value of 173 - is not healthy, but is unknown

• how does alpha diversity change with relation to sample type?

The vertical lines on the plot (i.e. figure 1c, figure S1) are actually not SD, instead its SE (dispersion of sample means around the population mean). Think I wrote in the MS that this is SD.