Last updated: 2022-09-23
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Knit directory: Immunue_Cell_Study/
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Rmd | 098d058 | Jie Zhou | 2022-09-20 | immune cell |
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source("./code/datacleaning.r")
index=which(longidata$time==6)
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
#if (length(which(y1>0))<=5){next}
fm=try({glm(cbind(y1,y2)~bcell + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver, data=longibcell[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~bcell + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver ,data=longibcell[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=p.adjust(rrbcell[,2],method = "BH")
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
2 Actinomyces -0.34144625 0.000000e+00 -0.348931638
6 Bacteroides 0.02521323 0.000000e+00 0.024487300
7 Bifidobacterium -0.04045805 0.000000e+00 -0.041313022
8 Blautia 0.13222197 0.000000e+00 0.130369250
11 Citrobacter -0.31228273 0.000000e+00 -0.318424016
14 Clostridium_XVIII 0.17770835 0.000000e+00 0.176316735
20 Enterobacter 0.16787844 0.000000e+00 0.165979878
21 Enterococcus -0.35742862 0.000000e+00 -0.359498191
24 F__Enterobacteriaceae -0.10599723 0.000000e+00 -0.107889353
25 F__Erysipelotrichaceae 0.40056202 0.000000e+00 0.391126535
31 Gemella 0.31656157 0.000000e+00 0.300701209
34 Intestinibacter -0.88189347 0.000000e+00 -0.916143031
35 Klebsiella 0.14821964 0.000000e+00 0.145811499
37 Lactobacillus -0.30081828 0.000000e+00 -0.303903400
40 Parabacteroides -0.24899323 0.000000e+00 -0.252227731
43 Raoultella 0.32893057 0.000000e+00 0.318341430
46 Staphylococcus 0.07376760 0.000000e+00 0.070109838
47 Streptococcus 0.14953248 0.000000e+00 0.148366931
44 Romboutsia -0.40857705 2.660370e-295 -0.430381189
49 Varibaculum -1.33743586 3.536215e-211 -1.421959289
50 Veillonella 0.02921007 3.457742e-208 0.027350704
13 Clostridium_XI -0.29489287 4.982304e-196 -0.314243732
16 Clostridium_sensu_stricto -0.02038129 1.560538e-189 -0.021741686
26 F__Lachnospiraceae 0.02882647 1.121700e-178 0.026844123
45 Rothia 0.22272989 1.876132e-170 0.207043614
17 Corynebacterium -0.28619192 1.790965e-121 -0.310125635
22 Escherichia/Shigella -0.01225394 6.240454e-116 -0.013303343
4 Anaerostipes -0.83029460 1.080759e-102 -0.905927002
1 Acinetobacter -0.35658882 4.717839e-62 -0.398632806
42 Propionibacterium -0.23553227 4.375787e-61 -0.263528709
38 Lactococcus -0.55510541 1.004179e-58 -0.622442611
5 Atopobium 0.12476066 9.732001e-40 0.106224619
12 Clostridium_IV -0.15368532 3.475926e-39 -0.176686688
19 Eggerthella -0.13202518 9.543765e-29 -0.155286582
41 Prevotella 0.19333556 1.630601e-25 0.157038339
9 Buttiauxella -0.20630904 1.591262e-23 -0.246762926
30 Fusobacterium 0.19232016 3.247494e-21 0.152450278
33 Haemophilus 0.03363840 5.941379e-20 0.026429167
32 Granulicatella -0.43759581 8.244933e-14 -0.552469563
15 Clostridium_XlVa -0.01177915 4.702560e-10 -0.015485709
3 Anaerococcus -0.07586561 3.097120e-06 -0.107745526
48 Terrisporobacter 0.02115181 2.752662e-04 0.009754635
36 Lachnoanaerobaculum -1.21952073 1.973596e-03 -1.992023569
27 Faecalibacterium -0.05810238 1.159112e-02 -0.103215169
51 Weissella 0.17141959 1.790992e-02 0.029503682
10 Chryseobacterium -0.17089786 2.630202e-02 -0.321663629
39 Negativicoccus 0.03228285 4.299860e-02 0.001016532
28 Finegoldia -0.04305268 5.039679e-02 -0.086180607
upper fdr
2 -3.339609e-01 0.000000e+00
6 2.593916e-02 0.000000e+00
7 -3.960308e-02 0.000000e+00
8 1.340747e-01 0.000000e+00
11 -3.061414e-01 0.000000e+00
14 1.791000e-01 0.000000e+00
20 1.697770e-01 0.000000e+00
21 -3.553590e-01 0.000000e+00
24 -1.041051e-01 0.000000e+00
25 4.099975e-01 0.000000e+00
31 3.324219e-01 0.000000e+00
34 -8.476439e-01 0.000000e+00
35 1.506278e-01 0.000000e+00
37 -2.977332e-01 0.000000e+00
40 -2.457587e-01 0.000000e+00
43 3.395197e-01 0.000000e+00
46 7.742537e-02 0.000000e+00
47 1.506980e-01 0.000000e+00
44 -3.867729e-01 7.140992e-295
49 -1.252912e+00 9.017347e-211
50 3.106943e-02 8.397373e-208
13 -2.755420e-01 1.154989e-195
16 -1.902089e-02 3.460323e-189
26 3.080882e-02 2.383612e-178
45 2.384162e-01 3.827309e-170
17 -2.622582e-01 3.513047e-121
22 -1.120455e-02 1.178752e-115
4 -7.546622e-01 1.968526e-102
1 -3.145448e-01 8.296889e-62
42 -2.075358e-01 7.438838e-61
38 -4.877682e-01 1.652036e-58
5 1.432967e-01 1.551038e-39
12 -1.306840e-01 5.371886e-39
19 -1.087638e-01 1.431565e-28
41 2.296328e-01 2.376019e-25
9 -1.658552e-01 2.254289e-23
30 2.321900e-01 4.476276e-21
33 4.084763e-02 7.973956e-20
32 -3.227220e-01 1.078184e-13
15 -8.072589e-03 5.995764e-10
3 -4.398569e-02 3.852515e-06
48 3.254898e-02 3.342518e-04
36 -4.470179e-01 2.340777e-03
27 -1.298958e-02 1.343516e-02
51 3.133355e-01 2.029791e-02
10 -2.013209e-02 2.916094e-02
39 6.354917e-02 4.665805e-02
28 7.523931e-05 5.354659e-02
<>
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
#if (length(which(y1>0))<=5){next}
fm=try({glm(cbind(y1,y2)~cd4t + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver, data=longicd4[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~cd4t + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longicd4[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=p.adjust(rrbcell[,2],method = "BY")
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
8 Bifidobacterium -0.090918188 0.000000e+00 -0.091431546
9 Blautia -0.196081646 0.000000e+00 -0.197611626
14 Clostridium_XVIII 0.137182454 0.000000e+00 0.135967576
16 Clostridium_sensu_stricto -0.135792834 0.000000e+00 -0.136860864
20 Enterobacter -0.179098524 0.000000e+00 -0.181760098
21 Enterococcus 0.015714683 0.000000e+00 0.014910465
22 Escherichia/Shigella 0.055831479 0.000000e+00 0.055190833
23 F__Enterobacteriaceae -0.069093747 0.000000e+00 -0.070189278
24 F__Erysipelotrichaceae -0.320615973 0.000000e+00 -0.327761776
25 F__Lachnospiraceae -0.082472288 0.000000e+00 -0.083972674
30 Haemophilus -0.175315059 0.000000e+00 -0.180241616
33 Lactobacillus 0.067574861 0.000000e+00 0.066105798
36 Parabacteroides 0.126520656 0.000000e+00 0.124210891
39 Pseudomonas -0.635328006 0.000000e+00 -0.642560489
45 Veillonella -0.140964052 0.000000e+00 -0.142426932
17 Corynebacterium -0.262582653 4.768488e-303 -0.276414073
43 Streptococcus -0.016071914 8.953322e-286 -0.016943896
31 Intestinibacter -0.186372601 6.568311e-218 -0.197965856
15 Clostridium_XlVa -0.025693188 3.046364e-191 -0.027400372
13 Clostridium_XI -0.068615102 1.636280e-124 -0.074281649
44 Varibaculum -0.269836771 1.786160e-122 -0.292308791
5 Anaerostipes 0.444183990 3.654335e-114 0.405846663
7 Bacteroides 0.005703242 1.080709e-104 0.005188809
1 Acinetobacter 0.176443013 6.925412e-94 0.159618579
12 Clostridium_IV -0.099539482 7.324775e-48 -0.112962538
10 Buttiauxella -0.164355219 6.962892e-45 -0.187271393
42 Staphylococcus 0.019020204 1.096377e-43 0.016330609
2 Actinomyces 0.028855488 1.462876e-37 0.024440044
34 Lactococcus -0.133429019 1.749052e-23 -0.159616856
40 Raoultella -0.029360146 8.871501e-23 -0.035217806
26 Faecalibacterium -0.112214316 1.078320e-18 -0.137131968
32 Klebsiella 0.008444617 5.402173e-17 0.006468936
37 Prevotella -0.104496816 1.407059e-14 -0.131110819
38 Propionibacterium -0.045742737 6.869898e-11 -0.059486306
6 Atopobium -0.055532452 7.480620e-10 -0.073214574
28 Gemella -0.042139809 1.244329e-06 -0.059174966
41 Rothia -0.037655778 1.635575e-06 -0.053051405
3 Anaerococcus 0.049983239 3.543648e-06 0.028853674
27 Finegoldia 0.069679334 6.374463e-06 0.039421374
11 Chryseobacterium -0.160693485 1.630617e-04 -0.244230747
35 Negativicoccus 0.044200246 4.807012e-04 0.019386330
4 Anaerosporobacter -0.151982987 1.794837e-02 -0.277849800
upper fdr
8 -0.090404830 0.000000e+00
9 -0.194551666 0.000000e+00
14 0.138397333 0.000000e+00
16 -0.134724803 0.000000e+00
20 -0.176436950 0.000000e+00
21 0.016518901 0.000000e+00
22 0.056472125 0.000000e+00
23 -0.067998216 0.000000e+00
24 -0.313470169 0.000000e+00
25 -0.080971903 0.000000e+00
30 -0.170388502 0.000000e+00
33 0.069043925 0.000000e+00
36 0.128830420 0.000000e+00
39 -0.628095522 0.000000e+00
45 -0.139501172 0.000000e+00
17 -0.248751232 5.894229e-302
43 -0.015199933 1.041601e-284
31 -0.174779345 7.216846e-217
15 -0.023986005 3.170987e-190
13 -0.062948555 1.618058e-123
44 -0.247364750 1.682160e-121
5 0.482521318 3.285126e-113
7 0.006217675 9.292816e-104
1 0.193267446 5.706905e-93
12 -0.086116426 5.794561e-47
10 -0.141439045 5.296422e-44
42 0.021709799 8.030870e-43
2 0.033270932 1.033275e-36
34 -0.107241183 1.192809e-22
40 -0.023502486 5.848468e-22
26 -0.087296663 6.879427e-18
32 0.010420298 3.338757e-16
37 -0.077882814 8.432658e-14
38 -0.031999168 3.996112e-10
6 -0.037850330 4.227035e-09
28 -0.025104652 6.835952e-06
41 -0.022260152 8.742490e-06
3 0.071112805 1.844307e-05
27 0.099937293 3.232550e-05
11 -0.077156223 8.062285e-04
35 0.069014163 2.318770e-03
4 -0.026116174 8.451661e-02
<>
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
#if (length(which(y1>0))<=5){next}
fm=try({glm(cbind(y1,y2)~cd8t + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longicd8[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~cd8t + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longicd8[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=p.adjust(rrbcell[,2],method = "BY")
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
1 Acinetobacter 0.618139024 0.000000e+00 0.600559331
7 Bacteroides -0.055116837 0.000000e+00 -0.055994411
8 Bifidobacterium -0.040736977 0.000000e+00 -0.041655889
9 Blautia -0.338149577 0.000000e+00 -0.340925778
14 Clostridium_XI 0.271347841 0.000000e+00 0.260799417
15 Clostridium_XVIII 0.237850086 0.000000e+00 0.236272026
21 Enterobacter 0.262403806 0.000000e+00 0.259903848
22 Enterococcus -0.057689379 0.000000e+00 -0.059117003
23 Escherichia/Shigella 0.035333097 0.000000e+00 0.034289903
25 F__Erysipelotrichaceae 0.305964333 0.000000e+00 0.292775064
26 F__Lachnospiraceae 0.088609586 0.000000e+00 0.086162723
33 Haemophilus 0.182142062 0.000000e+00 0.173338900
35 Klebsiella -0.093635689 0.000000e+00 -0.097489097
36 Lactobacillus -0.156798118 0.000000e+00 -0.159726183
39 Parabacteroides -0.083569740 0.000000e+00 -0.086715450
42 Raoultella 0.408139861 0.000000e+00 0.394968707
43 Romboutsia 0.389277583 0.000000e+00 0.374233374
45 Staphylococcus 0.106341284 0.000000e+00 0.102739334
46 Streptococcus 0.146847625 0.000000e+00 0.145451962
48 Veillonella 0.062549925 0.000000e+00 0.060400072
31 Gemella 0.475388483 6.364785e-304 0.450383930
16 Clostridium_XlVa -0.052977336 2.221398e-199 -0.056424061
13 Clostridium_IV -0.526030920 4.606198e-193 -0.560816060
38 Negativicoccus 0.577367197 1.092186e-152 0.534373998
6 Atopobium 0.284109408 2.378025e-144 0.262342554
44 Rothia 0.267794018 1.233621e-134 0.246538999
24 F__Enterobacteriaceae 0.021974530 1.123863e-130 0.020203763
2 Actinomyces -0.077044982 3.120652e-108 -0.083877753
5 Anaerostipes 0.408967130 4.274362e-92 0.369585509
20 Eggerthella -0.194377752 1.784306e-59 -0.217802857
3 Anaerococcus -0.266739855 2.222648e-44 -0.304150884
30 Fusobacterium 0.512655625 1.938680e-40 0.437181552
10 Buttiauxella -0.251003394 7.482938e-40 -0.288239798
12 Citrobacter -0.027311721 6.672667e-36 -0.031591146
17 Clostridium_sensu_stricto -0.007931711 1.929997e-25 -0.009423114
37 Lactococcus -0.213635867 4.099873e-21 -0.258039381
18 Corynebacterium -0.081659054 4.892338e-13 -0.103801565
41 Propionibacterium -0.094335340 1.420061e-10 -0.123163714
28 Finegoldia -0.160577717 1.186921e-09 -0.212325874
47 Varibaculum 0.072329805 9.995512e-08 0.045716027
27 Faecalibacterium -0.088987317 9.161475e-05 -0.133574364
4 Anaerosporobacter -0.307276813 1.074628e-04 -0.462775938
34 Intestinibacter 0.024598841 1.043331e-03 0.009893139
49 Weissella 0.346532861 1.221248e-03 0.136504543
upper fdr
1 0.635718718 0.000000e+00
7 -0.054239263 0.000000e+00
8 -0.039818064 0.000000e+00
9 -0.335373376 0.000000e+00
14 0.281896264 0.000000e+00
15 0.239428146 0.000000e+00
21 0.264903764 0.000000e+00
22 -0.056261754 0.000000e+00
23 0.036376291 0.000000e+00
25 0.319153601 0.000000e+00
26 0.091056449 0.000000e+00
33 0.190945225 0.000000e+00
35 -0.089782281 0.000000e+00
36 -0.153870053 0.000000e+00
39 -0.080424031 0.000000e+00
42 0.421311015 0.000000e+00
43 0.404321793 0.000000e+00
45 0.109943233 0.000000e+00
46 0.148243288 0.000000e+00
48 0.064699779 0.000000e+00
31 0.500393037 6.652142e-303
16 -0.049530612 2.216158e-198
13 -0.491245780 4.395536e-192
38 0.620360396 9.988086e-152
6 0.305876261 2.087726e-143
44 0.289049036 1.041371e-133
24 0.023745296 9.135800e-130
2 -0.070212211 2.446157e-107
5 0.448348751 3.234970e-91
20 -0.170952646 1.305405e-58
3 -0.229328826 1.573643e-43
30 0.588129698 1.329699e-39
10 -0.213766989 4.976858e-39
12 -0.023032297 4.307424e-35
17 -0.006440307 1.210280e-24
37 -0.169232352 2.499568e-20
18 -0.059516544 2.902096e-12
41 -0.065506966 8.202015e-10
28 -0.108829560 6.679656e-09
47 0.098943583 5.484564e-07
27 -0.044400270 4.904318e-04
4 -0.151777688 5.615729e-04
34 0.039304544 5.325383e-03
49 0.556561179 6.091835e-03
<>
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
# if (length(which(y1>0))<=5) {next}
fm=try({glm(cbind(y1,y2)~mono + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longimono[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~mono + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longimono[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=p.adjust(rrbcell[,2],method = "BH")
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
1 Actinomyces -0.592813608 0.000000e+00 -0.60346339
6 Bacteroides 0.043428412 0.000000e+00 0.04249312
7 Bifidobacterium -0.176807070 0.000000e+00 -0.17785695
11 Citrobacter 0.106603559 0.000000e+00 0.10174602
14 Clostridium_XVIII 0.243825011 0.000000e+00 0.24192901
15 Clostridium_XlVa 0.131441935 0.000000e+00 0.12798814
16 Clostridium_sensu_stricto 0.053454622 0.000000e+00 0.05162849
20 Enterobacter -0.184762273 0.000000e+00 -0.18899373
21 Enterococcus -0.160696126 0.000000e+00 -0.16254621
22 Escherichia/Shigella 0.036508503 0.000000e+00 0.03537755
24 F__Erysipelotrichaceae -0.574651061 0.000000e+00 -0.58745145
25 F__Lachnospiraceae -0.407407675 0.000000e+00 -0.41116700
31 Haemophilus 0.277942525 0.000000e+00 0.26810885
33 Klebsiella 0.194675985 0.000000e+00 0.19078729
35 Lactobacillus -0.078151131 0.000000e+00 -0.08126807
38 Parabacteroides -0.174669411 0.000000e+00 -0.17866429
41 Romboutsia 0.771589285 0.000000e+00 0.75169875
43 Ruminococcus2 0.321772839 0.000000e+00 0.30567753
44 Staphylococcus 0.099712710 0.000000e+00 0.09522824
47 Veillonella -0.075218369 0.000000e+00 -0.07790735
45 Streptococcus 0.033219523 6.221763e-305 0.03147515
32 Intestinibacter -0.379888355 2.039874e-228 -0.40296407
23 F__Enterobacteriaceae 0.031108915 1.952919e-204 0.02911040
29 Gemella -0.549532117 1.337337e-169 -0.58833260
12 Clostridium_IV 0.217368525 6.542925e-130 0.19980008
4 Anaerostipes -0.532614759 1.129089e-103 -0.58089670
40 Propionibacterium 0.240321581 2.803970e-79 0.21533652
42 Rothia -0.284579084 9.710402e-68 -0.31665233
28 Fusobacterium 0.643673516 3.892558e-54 0.56224106
19 Eggerthella -0.153522043 1.163418e-33 -0.17840642
46 Varibaculum -0.190924804 1.096007e-25 -0.22664063
26 Faecalibacterium 0.157983109 2.622333e-13 0.11563819
39 Prevotella 0.176110990 6.258787e-12 0.12589335
3 Anaerosporobacter -0.783074165 1.935495e-09 -1.03874502
27 Finegoldia 0.124567313 1.145117e-08 0.08179144
36 Lactococcus 0.098297658 4.184769e-06 0.05643240
37 Negativicoccus -0.090748966 2.305249e-05 -0.13276766
13 Clostridium_XI 0.031784664 2.666902e-05 0.01695249
48 Weissella 0.514078543 9.721851e-05 0.25555082
9 Buttiauxella 0.063281734 8.802510e-04 0.02599276
18 Dolosigranulum -0.192254500 1.002732e-03 -0.30679748
2 Anaerococcus -0.046232260 5.905273e-03 -0.07914740
5 Atopobium 0.040948114 6.990341e-03 0.01119311
17 Corynebacterium -0.024261119 5.174509e-02 -0.04870622
8 Blautia -0.002423507 5.267185e-02 -0.00487503
upper fdr
1 -0.5821638225 0.000000e+00
6 0.0443637088 0.000000e+00
7 -0.1757571879 0.000000e+00
11 0.1114610951 0.000000e+00
14 0.2457210112 0.000000e+00
15 0.1348957303 0.000000e+00
16 0.0552807561 0.000000e+00
20 -0.1805308187 0.000000e+00
21 -0.1588460400 0.000000e+00
22 0.0376394517 0.000000e+00
24 -0.5618506710 0.000000e+00
25 -0.4036483538 0.000000e+00
31 0.2877761958 0.000000e+00
33 0.1985646809 0.000000e+00
35 -0.0750341917 0.000000e+00
38 -0.1706745327 0.000000e+00
41 0.7914798252 0.000000e+00
43 0.3378681506 0.000000e+00
44 0.1041971782 0.000000e+00
47 -0.0725293903 0.000000e+00
45 0.0349638918 1.422117e-304
32 -0.3568126435 4.450633e-228
23 0.0331074261 4.075657e-204
29 -0.5107316315 2.674673e-169
12 0.2349369665 1.256242e-129
4 -0.4843328170 2.084472e-103
40 0.2653066415 4.984835e-79
42 -0.2525058389 1.664640e-67
28 0.7251059734 6.442854e-54
19 -0.1286376670 1.861470e-33
46 -0.1552089790 1.697044e-25
26 0.2003280302 3.933499e-13
39 0.2263286306 9.103690e-12
3 -0.5274033144 2.732463e-09
27 0.1673431848 1.570446e-08
36 0.1401629135 5.579692e-06
37 -0.0487302740 2.990593e-05
13 0.0466168340 3.368718e-05
48 0.7726062617 1.196535e-04
9 0.1005707093 1.056301e-03
18 -0.0777115201 1.173930e-03
2 -0.0133171194 6.748884e-03
5 0.0707031225 7.803172e-03
17 0.0001839819 5.618330e-02
8 0.0000280154 5.618330e-02
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
#if (length(which(y1>0))<=5) {next}
fm=try({glm(cbind(y1,y2)~nk + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longink[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~nk + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver, data=longink[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=p.adjust(rrbcell[,2],method = "BH")
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
2 Actinomyces 0.10784266 0.000000e+00 0.103898462
7 Bacteroides -0.06568714 0.000000e+00 -0.066417182
8 Bifidobacterium -0.18344675 0.000000e+00 -0.184346651
14 Clostridium_XlVa -0.19408955 0.000000e+00 -0.197411318
15 Clostridium_sensu_stricto 0.07366859 0.000000e+00 0.072618585
16 Corynebacterium -0.82365026 0.000000e+00 -0.859503966
19 Enterobacter -0.06756688 0.000000e+00 -0.069965697
20 Enterococcus 0.02816841 0.000000e+00 0.027082461
21 Escherichia/Shigella -0.13991086 0.000000e+00 -0.141003043
22 F__Enterobacteriaceae 0.26550851 0.000000e+00 0.264182935
23 F__Erysipelotrichaceae 0.22814064 0.000000e+00 0.222342553
33 Lactobacillus -0.19257079 0.000000e+00 -0.195100351
36 Parabacteroides 0.05602170 0.000000e+00 0.053420761
42 Staphylococcus -0.09077586 0.000000e+00 -0.094705115
43 Streptococcus 0.11723465 0.000000e+00 0.116137463
44 Terrisporobacter 0.18230703 0.000000e+00 0.176223994
46 Veillonella 0.06536742 0.000000e+00 0.063642937
38 Propionibacterium -0.71958476 7.334505e-210 -0.765205054
1 Acinetobacter -0.50644054 3.449519e-197 -0.539574253
13 Clostridium_XVIII 0.02189419 7.054038e-171 0.020354181
30 Haemophilus -0.09845382 1.965803e-140 -0.106102785
12 Clostridium_XI 0.10636601 3.667387e-115 0.097226184
24 F__Lachnospiraceae 0.02406540 8.078137e-114 0.021985129
32 Klebsiella -0.02402994 3.776801e-61 -0.026884707
11 Clostridium_IV 0.11062854 4.217319e-28 0.090900590
18 Eggerthella 0.07750253 7.536862e-25 0.062745191
39 Raoultella 0.04011859 1.834332e-23 0.032240869
29 Granulicatella 0.32401160 1.763453e-22 0.258907480
3 Anaerococcus 0.09112504 1.008559e-15 0.068871206
5 Anaerotruncus -0.41369393 8.372112e-15 -0.518159174
6 Atopobium -0.07804846 1.168621e-12 -0.099566866
9 Buttiauxella -0.08168416 3.145970e-10 -0.107131716
27 Fusobacterium 0.12677482 4.551002e-09 0.084392643
26 Finegoldia -0.10416373 3.378428e-08 -0.141145375
31 Intestinibacter -0.03951684 9.193849e-08 -0.054015781
40 Romboutsia 0.02200140 2.610349e-07 0.013627410
47 Weissella 0.33372555 6.713728e-05 0.169634302
25 Faecalibacterium -0.07286169 2.352893e-04 -0.111692075
4 Anaerostipes -0.07452608 7.428870e-04 -0.117828975
41 Rothia -0.02870778 4.373695e-03 -0.048451574
17 Dolosigranulum -0.09372324 1.551662e-02 -0.169628464
10 Chryseobacterium 0.07899173 3.146204e-02 0.007020147
28 Gemella -0.01895419 4.584190e-02 -0.037558627
upper fdr
2 0.1117868560 0.000000e+00
7 -0.0649570995 0.000000e+00
8 -0.1825468413 0.000000e+00
14 -0.1907677773 0.000000e+00
15 0.0747185918 0.000000e+00
16 -0.7877965478 0.000000e+00
19 -0.0651680732 0.000000e+00
20 0.0292543566 0.000000e+00
21 -0.1388186727 0.000000e+00
22 0.2668340796 0.000000e+00
23 0.2339387286 0.000000e+00
33 -0.1900412331 0.000000e+00
36 0.0586226488 0.000000e+00
42 -0.0868466059 0.000000e+00
43 0.1183318466 0.000000e+00
44 0.1883900637 0.000000e+00
46 0.0670918999 0.000000e+00
38 -0.6739644680 1.915121e-209
1 -0.4733068349 8.533021e-197
13 0.0234341981 1.657699e-170
30 -0.0908048569 4.399653e-140
12 0.1155058372 7.834872e-115
24 0.0261456698 1.650750e-113
32 -0.0211751706 7.396235e-61
11 0.1303564833 7.928560e-28
18 0.0922598626 1.362433e-24
39 0.0479963019 3.193097e-23
29 0.3891157194 2.960083e-22
3 0.1133788649 1.634562e-15
5 -0.3092286876 1.311631e-14
6 -0.0565300527 1.771780e-12
9 -0.0562366119 4.620644e-10
27 0.1691570049 6.481730e-09
26 -0.0671820805 4.670179e-08
31 -0.0250178987 1.234603e-07
40 0.0303753882 3.407955e-07
47 0.4978168052 8.528249e-05
25 -0.0340313071 2.910157e-04
4 -0.0312231913 8.952740e-04
41 -0.0089639939 5.139092e-03
17 -0.0178180171 1.778735e-02
10 0.1509633200 3.520752e-02
28 -0.0003497456 5.010626e-02
<>
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
if (length(which(y1>0))<=5) {next}
fm=try({glm(cbind(y1,y2)~nrbc + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longinrbc[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~nrbc + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longinrbc[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=c(r1,r2,r3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=round(p.adjust(rrbcell[,2],method = "BH"),3)
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower
1 Acinetobacter -0.341264407 0.000000e+00 -0.353971704
2 Actinomyces 0.093471034 0.000000e+00 0.091363919
6 Bacteroides -0.031958952 0.000000e+00 -0.032376000
7 Bifidobacterium 0.024012797 0.000000e+00 0.023694804
12 Clostridium_XI -0.128664565 0.000000e+00 -0.135282469
13 Clostridium_XVIII 0.033996343 0.000000e+00 0.033302073
14 Clostridium_XlVa -0.041476034 0.000000e+00 -0.042400025
19 Enterobacter 0.044494710 0.000000e+00 0.043282311
21 Escherichia/Shigella -0.017471113 0.000000e+00 -0.017883308
22 F__Enterobacteriaceae 0.040391249 0.000000e+00 0.039797178
23 F__Erysipelotrichaceae 0.154590355 0.000000e+00 0.151119890
24 F__Lachnospiraceae 0.121007383 0.000000e+00 0.120116816
27 Flavonifractor 0.102782608 0.000000e+00 0.100950983
29 Haemophilus -0.175327651 0.000000e+00 -0.181999642
35 Parabacteroides 0.106644232 0.000000e+00 0.105184169
40 Staphylococcus -0.104415611 0.000000e+00 -0.106590587
41 Streptococcus -0.009360334 2.462089e-274 -0.009878742
32 Lactobacillus 0.012179016 4.051566e-213 0.011412873
10 Citrobacter 0.026502245 1.420982e-211 0.024828937
30 Intestinibacter 0.087579802 2.853883e-181 0.081600847
31 Klebsiella -0.025835433 2.707129e-171 -0.027650430
8 Blautia -0.012591039 3.937935e-167 -0.013486670
4 Anaerostipes 0.203206503 2.342309e-137 0.187240818
16 Corynebacterium -0.170856896 8.684623e-126 -0.184894182
20 Enterococcus 0.003885366 2.393369e-79 0.003481603
3 Anaerococcus -0.152885592 2.034103e-77 -0.168974930
37 Propionibacterium -0.120115834 3.599571e-71 -0.133314088
28 Gemella 0.084821002 3.053271e-70 0.075437860
34 Negativicoccus -0.179557507 1.912931e-59 -0.201202251
18 Eggerthella 0.069043389 4.225612e-59 0.060695592
11 Clostridium_IV -0.027289711 5.932358e-35 -0.031626281
43 Veillonella 0.004384751 3.539929e-25 0.003555685
15 Clostridium_sensu_stricto 0.002656663 2.685057e-23 0.002133012
25 Faecalibacterium 0.064272381 5.533227e-18 0.049695116
26 Finegoldia -0.081963168 1.039043e-17 -0.100709556
42 Varibaculum 0.034902026 1.652257e-10 0.024197575
39 Ruminococcus2 -0.022743599 3.784366e-10 -0.029861560
33 Lactococcus -0.048612859 1.119969e-09 -0.064255035
36 Prevotella 0.061617498 1.137242e-09 0.041782835
5 Atopobium -0.030181500 4.347642e-07 -0.041888391
38 Rothia 0.015415764 8.819359e-04 0.006330517
17 Dolosigranulum -0.060788659 9.391239e-03 -0.106658530
upper fdr
1 -0.328557111 0.000
2 0.095578149 0.000
6 -0.031541905 0.000
7 0.024330789 0.000
12 -0.122046662 0.000
13 0.034690612 0.000
14 -0.040552043 0.000
19 0.045707109 0.000
21 -0.017058918 0.000
22 0.040985320 0.000
23 0.158060821 0.000
24 0.121897950 0.000
27 0.104614234 0.000
29 -0.168655659 0.000
35 0.108104295 0.000
40 -0.102240636 0.000
41 -0.008841927 0.000
32 0.012945159 0.000
10 0.028175553 0.000
30 0.093558757 0.000
31 -0.024020437 0.000
8 -0.011695407 0.000
4 0.219172189 0.000
16 -0.156819609 0.000
20 0.004289129 0.000
3 -0.136796254 0.000
37 -0.106917580 0.000
28 0.094204144 0.000
34 -0.157912763 0.000
18 0.077391187 0.000
11 -0.022953141 0.000
43 0.005213818 0.000
15 0.003180314 0.000
25 0.078849646 0.000
26 -0.063216781 0.000
42 0.045606478 0.000
39 -0.015625638 0.000
33 -0.032970682 0.000
36 0.081452160 0.000
5 -0.018474609 0.000
38 0.024501011 0.001
17 -0.014918788 0.010
<>
options(warn = 2)
m=ncol(longidata)-2
n=nrow(longidata)
name=colnames(longidata)[-c(1,2)]
microbe=c()
rrbcell=data.frame()
for (k in 1:m) {
y1=longidata[index,k+2]
y2=apply(longidata[index,-c(1,2,k+2)],1,sum)
#if (length(which(y1>0))<=5) {next}
fm=try({glm(cbind(y1,y2)~gran + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longigran[index,],family="binomial")},silent = T)
if (inherits(fm,"try-error")){
next()
}else{
fm=glm(cbind(y1,y2)~gran + bbymale + enrollment_age + imrbthwghtg_all +gestage_all+evercigpreg+alpha+deliver , data=longigran[index,],family="binomial")
a=summary(fm)
r1=a$coefficients[2,1]
r2=a$coefficients[2,4]
r3= c(r1-1.96*a$coefficients[2,2],r1+ 1.96*a$coefficients[2,2])
rr=round(c(r1,r2,r3),3)
microbe=c(microbe,name[k])
rrbcell=rbind(rrbcell,rr)
}
}
colnames(rrbcell)=c("coef","pvalue","lower","upper")
fdr=round(p.adjust(rrbcell[,2],method = "BH"),3)
rrbcell=data.frame(microbe,rrbcell,fdr)
rrbcell=rrbcell[order(rrbcell[,3]),]
rrbcellfdr=rrbcell[which(rrbcell[,6]<0.1),]
microbe coef pvalue lower upper fdr
1 Acinetobacter -0.099 0.000 -0.109 -0.090 0.000
2 Actinomyces -0.029 0.000 -0.031 -0.028 0.000
3 Anaerococcus 0.075 0.000 0.065 0.085 0.000
5 Anaerostipes -0.152 0.000 -0.164 -0.140 0.000
6 Atopobium -0.015 0.000 -0.021 -0.008 0.000
7 Bacteroides 0.012 0.000 0.012 0.012 0.000
8 Bifidobacterium 0.050 0.000 0.050 0.050 0.000
9 Blautia 0.029 0.000 0.028 0.030 0.000
10 Buttiauxella 0.071 0.000 0.061 0.081 0.000
11 Chryseobacterium -0.053 0.000 -0.078 -0.027 0.000
12 Citrobacter 0.013 0.000 0.012 0.014 0.000
13 Clostridium_IV 0.115 0.000 0.107 0.122 0.000
14 Clostridium_XI 0.100 0.000 0.095 0.105 0.000
15 Clostridium_XVIII -0.080 0.000 -0.080 -0.079 0.000
16 Clostridium_XlVa 0.133 0.000 0.131 0.134 0.000
17 Clostridium_sensu_stricto 0.001 0.000 0.001 0.001 0.000
18 Corynebacterium 0.234 0.000 0.225 0.243 0.000
20 Eggerthella -0.025 0.000 -0.031 -0.018 0.000
21 Enterobacter -0.028 0.000 -0.029 -0.027 0.000
22 Enterococcus 0.019 0.000 0.018 0.019 0.000
23 Escherichia/Shigella 0.005 0.000 0.005 0.005 0.000
24 F__Enterobacteriaceae -0.033 0.000 -0.034 -0.033 0.000
25 F__Erysipelotrichaceae -0.095 0.000 -0.097 -0.092 0.000
26 F__Lachnospiraceae -0.033 0.000 -0.034 -0.033 0.000
28 Finegoldia 0.048 0.000 0.035 0.062 0.000
30 Gemella -0.078 0.000 -0.084 -0.072 0.000
31 Granulicatella -0.103 0.000 -0.125 -0.080 0.000
32 Haemophilus 0.051 0.000 0.048 0.053 0.000
33 Intestinibacter 0.056 0.000 0.050 0.062 0.000
34 Klebsiella -0.013 0.000 -0.014 -0.012 0.000
35 Lactobacillus 0.032 0.000 0.031 0.033 0.000
36 Lactococcus 0.148 0.000 0.130 0.167 0.000
38 Parabacteroides -0.031 0.000 -0.032 -0.030 0.000
39 Prevotella -0.037 0.000 -0.050 -0.024 0.000
40 Propionibacterium 0.103 0.000 0.095 0.111 0.000
41 Romboutsia 0.232 0.000 0.226 0.238 0.000
42 Rothia -0.028 0.000 -0.034 -0.023 0.000
43 Staphylococcus 0.031 0.000 0.029 0.032 0.000
44 Streptococcus -0.031 0.000 -0.031 -0.030 0.000
45 Varibaculum 0.144 0.000 0.132 0.156 0.000
46 Veillonella 0.009 0.000 0.008 0.009 0.000
19 Dolosigranulum 0.027 0.037 0.002 0.052 0.041
27 Faecalibacterium -0.013 0.042 -0.025 0.000 0.045
37 Negativicoccus -0.009 0.072 -0.019 0.001 0.075
<>
sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] vegan_2.6-2 lattice_0.20-45 permute_0.9-7
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 pillar_1.8.0 compiler_4.1.2 bslib_0.4.0
[5] later_1.3.0 jquerylib_0.1.4 git2r_0.30.1 workflowr_1.7.0
[9] tools_4.1.2 digest_0.6.29 nlme_3.1-153 jsonlite_1.8.0
[13] evaluate_0.15 lifecycle_1.0.1 tibble_3.1.7 mgcv_1.8-38
[17] pkgconfig_2.0.3 rlang_1.0.4 Matrix_1.3-4 cli_3.3.0
[21] rstudioapi_0.13 parallel_4.1.2 yaml_2.3.5 xfun_0.31
[25] fastmap_1.1.0 cluster_2.1.2 stringr_1.4.0 knitr_1.39
[29] fs_1.5.2 vctrs_0.4.1 sass_0.4.2 grid_4.1.2
[33] rprojroot_2.0.3 glue_1.6.2 R6_2.5.1 fansi_1.0.3
[37] rmarkdown_2.14 magrittr_2.0.3 whisker_0.4 splines_4.1.2
[41] MASS_7.3-54 promises_1.2.0.1 ellipsis_0.3.2 htmltools_0.5.2
[45] httpuv_1.6.5 utf8_1.2.2 stringi_1.7.6 cachem_1.0.6