[                       Extract 'marker_table' object
abundances              Extract taxa abundances
aggregate_taxa          Aggregate Taxa
assign-otu_table        Assign a new OTU table
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.
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
marker_table            Build or access the marker_table
marker_table-class      The S4 class for storing microbiome marker
                        information
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
normalize,phyloseq-method
                        Normalize the microbial abundance data
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_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
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
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
