# microbiome biomarker analysis toolkit

## Documentation for package ‘microbiomeMarker’ version 1.8.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

abundances | Extract taxa abundances
abundances, | Extract taxa abundances
abundances-method | Extract taxa abundances
aggregate_taxa | Aggregate Taxa
assign-marker_table | Assign marker_table to 'object'
assign-otu_table | Assign a new OTU table
caporaso | 16S rRNA data from "Moving pictures of the human microbiome"
cid_ying | 16S rRNA data of 94 patients from CID 2012
compare_DA | Comparing the results of differential analysis methods by Empirical power and False Discovery Rate
confounder | Confounder analysis
data-caporaso | 16S rRNA data from "Moving pictures of the human microbiome"
data-cid_ying | 16S rRNA data of 94 patients from CID 2012
data-ecam | Data from Early Childhood Antibiotics and the Microbiome (ECAM) study
data-enterotypes_arumugam | Enterotypes data of 39 samples
data-kostic_crc | Data from a study on colorectal cancer (kostic 2012)
data-oxygen | Oxygen availability 16S dataset, of which taxa table has been summarized for python lefse input
data-pediatric_ibd | IBD stool samples
data-spontaneous_colitis | This is a sample data from lefse python script, a 16S dataset for studying the characteristics of the fecal microbiota in a mouse model of spontaneous colitis.
ecam | Data from Early Childhood Antibiotics and the Microbiome (ECAM) study
ef-barplot,ef-dotplot | bar and dot plot of effect size of microbiomeMarker data
enterotypes_arumugam | Enterotypes data of 39 samples
extract_posthoc_res | Extract results from a posthoc test
import_dada2 | Import function to read the the output of dada2 as phyloseq object
import_picrust2 | Import function to read the output of picrust2 as phyloseq object
import_qiime2 | Import function to read the the output of dada2 as phyloseq object
kostic_crc | Data from a study on colorectal cancer (kostic 2012)
marker_table | Build or access the marker_table
marker_table-class | The S4 class for storing microbiome marker information
marker_table-method | Build or access the marker_table
marker_table<- | Assign marker_table to 'object'
microbiomeMarker | Build microbiomeMarker-class objects
microbiomeMarker-class | The main class for microbiomeMarker data
nmarker | Get the number of microbiome markers
nmarker-method | Get the number of microbiome markers
normalize | Normalize the microbial abundance data
normalize-method | Normalize the microbial abundance data
norm_clr | Normalize the microbial abundance data
norm_cpm | Normalize the microbial abundance data
norm_css | Normalize the microbial abundance data
norm_rarefy | Normalize the microbial abundance data
norm_rle | Normalize the microbial abundance data
norm_tmm | Normalize the microbial abundance data
norm_tss | Normalize the microbial abundance data
otu_table-method | Extract taxa abundances
otu_table2metagenomeSeq | Convert phyloseq data to MetagenomeSeq 'MRexperiment' object
otu_table<--method | Assign a new OTU table
oxygen | Oxygen availability 16S dataset, of which taxa table has been summarized for python lefse input
pediatric_ibd | IBD stool samples
phyloseq2DESeq2 | Convert 'phyloseq-class' object to 'DESeqDataSet-class' object
phyloseq2edgeR | Convert phyloseq data to edgeR 'DGEList' object
phyloseq2metagenomeSeq | Convert phyloseq data to MetagenomeSeq 'MRexperiment' object
plot.compareDA | Plotting DA comparing result
plot_abundance | plot the abundances of markers
plot_cladogram | plot cladogram of micobiomeMaker results
plot_ef_bar | bar and dot plot of effect size of microbiomeMarker data
plot_ef_dot | bar and dot plot of effect size of microbiomeMarker data
plot_heatmap | Heatmap of microbiome marker
plot_postHocTest | 'postHocTest' plot
plot_sl_roc | ROC curve of microbiome marker from supervised learning methods
postHocTest | Build postHocTest object
postHocTest-class | The postHocTest Class, represents the result of post-hoc test result among multiple groups
postHocTest-method | The postHocTest Class, represents the result of post-hoc test result among multiple groups
run_aldex | Perform differential analysis using ALDEx2
run_ancom | Perform differential analysis using ANCOM
run_ancombc | Differential analysis of compositions of microbiomes with bias correction (ANCOM-BC).
run_deseq2 | Perform DESeq differential analysis
run_edger | Perform differential analysis using edgeR
run_lefse | Liner discriminant analysis (LDA) effect size (LEFSe) analysis
run_limma_voom | Differential analysis using limma-voom
run_marker | Find makers (differentially expressed metagenomic features)
run_metagenomeseq | metagenomeSeq differential analysis
run_posthoc_test | Post hoc pairwise comparisons for multiple groups test.
run_simple_stat | Simple statistical analysis of metagenomic profiles
run_sl | Identify biomarkers using supervised leaning (SL) methods
run_test_multiple_groups | Statistical test for multiple groups
run_test_two_groups | Statistical test between two groups
show, | The postHocTest Class, represents the result of post-hoc test result among multiple groups
show-method | The main class for microbiomeMarker data
show-method | The postHocTest Class, represents the result of post-hoc test result among multiple groups
spontaneous_colitis | This is a sample data from lefse python script, a 16S dataset for studying the characteristics of the fecal microbiota in a mouse model of spontaneous colitis.
subset_marker | Subset microbiome markers
summarize_taxa | Summarize taxa into a taxonomic level within each sample
summary.compareDA | Summary differential analysis methods comparison results
transform_abundances | Transform the taxa abundances in 'otu_table' sample by sample
[ | Extract 'marker_table' object
[-method | Extract 'marker_table' object