microbiome biomarker analysis toolkit

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Documentation for package ‘microbiomeMarker’ version 1.12.2

• 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