microbiome biomarker analysis toolkit

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Documentation for package ‘microbiomeMarker’ version 1.4.0

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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