kegg.12: Pathway abundance data.

Description Usage Format Source References Examples

Description

KEGG pathway abundance data from PICRUSt analysis. This is monthly longitudinal data of 50 infants from birth to 2 years of life.

Usage

1

Format

A list of 2 dataframes for level 1 and level 2 of KEGG pathways.

Source

Gordon Lab

References

Subramanian et al. Nature. 2014 Jun 19; 510(7505): 417–421. (PubMed)

Examples

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data(kegg.12)
# Load covariate data
data(covar.rm)
# Comparison of pathway relative abundances for some first pathways of level 1 only
# and assuming crosssectional data (to save running time)
path1<-pathway.compare(pathtab=list(kegg.12[[1]][, 1:2]),
mapfile=covar.rm,sampleid="sampleid",pathsum="rel", stat.med="gamlss",
comvar="gender",adjustvar=c("age.sample","bf"), longitudinal="no",
p.adjust.method="fdr", percent.filter=0.05,relabund.filter=0.00005)
taxcomtab.show(taxcomtab=path1$l1, sumvar="path",tax.lev="l2",
tax.select="none", showvar="genderMale", p.adjust.method="fdr",p.cutoff=1)

Example output

Loading required package: gamlss
Loading required package: splines
Loading required package: gamlss.data

Attaching package:gamlss.dataThe following object is masked frompackage:datasets:

    sleep

Loading required package: gamlss.dist
Loading required package: MASS
Loading required package: nlme
Loading required package: parallel
 **********   GAMLSS Version 5.2-0  ********** 
For more on GAMLSS look at https://www.gamlss.com/
Type gamlssNews() to see new features/changes/bug fixes.

[1] 1
******************************************************************
Family:  c("BEZI", "Zero Inflated Beta") 

Call:  gamlss::gamlss(formula = stats::as.formula(paste(pathname[i],  
    paste(c(comvar, adjustvar), collapse = "+"), sep = "~")),  
    family = BEZI, data = testdat, trace = FALSE) 

Fitting method: RS() 

------------------------------------------------------------------
Mu link function:  logit
Mu Coefficients:
                   Estimate Std. Error  t value Pr(>|t|)    
(Intercept)       -2.246380   0.019984 -112.410  < 2e-16 ***
genderMale         0.004272   0.014308    0.299    0.765    
age.sample         0.008404   0.001235    6.804 1.76e-11 ***
bfNon_exclusiveBF -0.022727   0.023196   -0.980    0.327    
bfNo_BF            0.042615   0.038138    1.117    0.264    
---
Signif. codes:  0***0.001**0.01*0.05.’ 0.1 ‘ ’ 1

------------------------------------------------------------------
Sigma link function:  log
Sigma Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  5.36087    0.04449   120.5   <2e-16 ***
---
Signif. codes:  0***0.001**0.01*0.05.’ 0.1 ‘ ’ 1

------------------------------------------------------------------
Nu link function:  logit 
Nu Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)   -21.43     866.54  -0.025     0.98

------------------------------------------------------------------
No. of observations in the fit:  995 
Degrees of Freedom for the fit:  7
      Residual Deg. of Freedom:  988 
                      at cycle:  7 
 
Global Deviance:     -4914.618 
            AIC:     -4900.618 
            SBC:     -4866.299 
******************************************************************
******************************************************************
Family:  c("BEZI", "Zero Inflated Beta") 

Call:  gamlss::gamlss(formula = stats::as.formula(paste(pathname[i],  
    paste(c(comvar, adjustvar), collapse = "+"), sep = "~")),  
    family = BEZI, data = testdat, trace = FALSE) 

Fitting method: RS() 

------------------------------------------------------------------
Mu link function:  logit
Mu Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)        2.246380   0.019984 112.410  < 2e-16 ***
genderMale        -0.004272   0.014308  -0.299    0.765    
age.sample        -0.008404   0.001235  -6.804 1.76e-11 ***
bfNon_exclusiveBF  0.022727   0.023196   0.980    0.327    
bfNo_BF           -0.042615   0.038138  -1.117    0.264    
---
Signif. codes:  0***0.001**0.01*0.05.’ 0.1 ‘ ’ 1

------------------------------------------------------------------
Sigma link function:  log
Sigma Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  5.36087    0.04449   120.5   <2e-16 ***
---
Signif. codes:  0***0.001**0.01*0.05.’ 0.1 ‘ ’ 1

------------------------------------------------------------------
Nu link function:  logit 
Nu Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)   -21.43     866.54  -0.025     0.98

------------------------------------------------------------------
No. of observations in the fit:  995 
Degrees of Freedom for the fit:  7
      Residual Deg. of Freedom:  988 
                      at cycle:  7 
 
Global Deviance:     -4914.618 
            AIC:     -4900.618 
            SBC:     -4866.299 
******************************************************************
Warning messages:
1: In summary.gamlss(gamlss::gamlss(stats::as.formula(paste(pathname[i],  :
  summary: vcov has failed, option qr is used instead

2: In summary.gamlss(gamlss::gamlss(stats::as.formula(paste(pathname[i],  :
  summary: vcov has failed, option qr is used instead

                                    id Estimate.genderMale    ll   ul
1                   Cellular.Processes                   0 -0.02 0.03
2 Environmental.Information.Processing                   0 -0.03 0.02
  Pr(>|t|).genderMale pval.adjust.genderMale
1              0.7654                 0.7654
2              0.7654                 0.7654

metamicrobiomeR documentation built on Nov. 9, 2020, 5:06 p.m.