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README.Rmd
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README.Rmd
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---
title:: R package for microbiome biomarker discovery
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
# microbiomeMarker
<a href='https://github.com/yiluheihei/microbiomeMarker'/><img src='man/figures/microbiomeMarker.png' height="150" align="right" style="float:right; height:150px;" />
<!-- badges: start -->
[](https://www.bioconductor.org/packages/microbiomeMarker)
[](https://github.com/yiluheihei/microbiomeMarker)
[](https://www.bioconductor.org/packages/devel/bioc/html/microbiomeMarker.html#archives)
[](https://bioconductor.org/checkResults/release/bioc-LATEST/microbiomeMarker)
[](https://www.bioconductor.org/packages/devel/bioc/html/microbiomeMarker.html#since)
[](https://github.com/yiluheihei/microbiomeMarker/actions)
[](https://github.com/yiluheihei/microbiomeMarker/blob/master/LICENSE.md)
[](https://codecov.io/gh/yiluheihei/microbiomeMarker?branch=master)
[](https://zenodo.org/badge/latestdoi/215731961)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
<!-- badges: end -->
***microbiomeMarker*** is still under development, your suggestion and contribution will be highly appreciated. If you think this project is helpful to you, you can give this project a :star:.
## Motivation
The aim of this package is to build a unified toolbox in R for microbiome
biomarker discovery by integrating existing widely used differential analysis methods.
## Installation
Install the package from Bioconductor directly:
```{r install-bioc,eval=FALSE}
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("microbiomeMarker")
```
Or install the development version of the package from
[Github](https://github.com/yiluheihei/microbiomeMarker).
```{r install-gh,eval=FALSE}
if (!requireNamespace("remotes", quietly=TRUE))
install.packages("remotes")
remotes::install_github("yiluheihei/microbiomeMarker")
```
For more details on how to use ***microbiomeMarker***, please see the help page
or [website](https://yiluheihei.github.io/microbiomeMarker/index.html) of our
package.
## Citation
Kindly cite as follows:
**Yang Cao**, Qingyang Dong, Dan Wang, Pengcheng Zhang, Ying Liu, Chao
Niu, microbiomeMarker: an R/Bioconductor package for microbiome marker
identification and visualization. Bioinformatics, 2022, btac438. doi: [10.1093/bioinformatics/btac438](https://doi.org/10.1093/bioinformatics/btac438)
Please cite the corresponding methods paper too:
- LEfSe: Segata, Nicola, Jacques Izard, et al. 2011. Metagenomic Biomarker
Discovery and Explanation. Genome Biology 12 (6): 1–18.
doi: [10.1186/gb-2011-12-6-r60](https://doi.org/10.1186/gb-2011-12-6-r60)
- metagenomeSeq: Paulson, Joseph N, O Colin Stine, et al. 2013. Differential
Abundance Analysis for Microbial Marker-Gene Surveys. Nature Methods 10 (12):
1200–1202. doi: [10.1038/nmeth.2658](https://doi.org/10.1038/nmeth.2658)
- ANCOM: Mandal, Siddhartha, Will Van Treuren, et al. 2015. Analysis of
Composition of Microbiomes: A Novel Method for Studying Microbial Composition.
Microbial Ecology in Health and Disease 26 (1): 27663.
doi: [10.3402/mehd.v26.27663](https://doi.org/10.3402/mehd.v26.27663)
- ANCOMBC: Lin, Huang, and Shyamal Das Peddada. 2020. Analysis of Compositions
of Microbiomes with Bias Correction. Nature Communications 11 (1): 1–11.
doi: [10.1038/s41522-020-00160-w](https://doi.org/10.1038/s41522-020-00160-w)
- ALDEx2: Fernandes, Andrew D, Jennifer Ns Reid, et al. 2014. Unifying the
Analysis of High-Throughput Sequencing Datasets: Characterizing Rna-Seq, 16S
rRNA Gene Sequencing and Selective Growth Experiments by Compositional Data
Analysis. Genome Biology 15(2): 1–17.
doi: [10.1186/2049-2618-2-15](https://doi.org/10.1186/2049-2618-2-15)
- edgeR: Robinson, Mark D, Davis J McCarthy, and Gordon K Smyth. 2010. EdgeR: A
Bioconductor Package for Differential Expression Analysis of Digital Gene
Expression Data. Bioinformatics 26 (1): 139–40. doi:
[10.1093/bioinformatics/btp616](https://doi.org/10.1093/bioinformatics/btp616)
- DESeq2: Love, Michael I, Wolfgang Huber, and Simon Anders. 2014. Moderated
Estimation of Fold Change and Dispersion for Rna-Seq Data with Deseq2. Genome
Biology 15 (12): 1–21.
doi: [10.1186/s13059-014-0550-8](https://doi.org/10.1186/s13059-014-0550-8)
- limma-voom: Law, Charity W, Yunshun Chen, et al. 2014. Voom: Precision Weights
Unlock Linear Model Analysis Tools for Rna-Seq Read Counts. Genome biology,
15(2), 1-17.
doi: [10.1186/gb-2014-15-2-r29](https://doi.org/10.1186/gb-2014-15-2-r29)
### Publications citing microbiomeMarker
- Jorge F, Froissard C, Dheilly N M, et al. Bacterial community dynamics
following antibiotic exposure in a trematode parasite. International
journal for parasitology, 2022, 52(5): 265-274.
https://doi.org/10.1016/j.ijpara.2021.11.006
- Ghosh A, Thakur M, Sharma L K, et al. Linking gut microbiome with the feeding
behavior of the Arunachal macaque (Macaca munzala). Scientific reports, 2021,
11(1): 1-10. https://doi.org/10.1038/s41598-021-01316-0
- Doi R, Wu Y, Kawai Y, et al. Transition and regulation mechanism of bacteria
biota in Kishu saba-narezushi (mackerel narezushi) during its fermentation
step. Journal of bioscience and bioengineering, 2021, 132(6): 606-612.
https://doi.org/10.1016/j.jbiosc.2021.09.002
- Nielsen K R, Ingham A C, Midjord J, et al. Similar Gut Bacterial Composition
Between Patients With Ulcerative Colitis and Healthy Controls in a High
Incidence Population: A Cross-sectional Study of the Faroe Islands IBD Cohort.
Inflammatory Bowel Diseases. https://doi.org/10.1093/ibd/izab355
- Prevel R, Enaud R, Orieux A, et al. Gut bacteriobiota and mycobiota are both
associated with Day-28 mortality among critically ill patients. Critical Care,
2022, 26(1): 1-9. https://doi.org/10.1186/s13054-022-03980-8
- Tandon K, Chiou Y J, Yu S P, et al. Microbiome restructuring: dominant coral
bacterium Endozoicomonas species display differential adaptive capabilities
to environmental changes[J]. bioRxiv, 2021.
https://doi.org/10.1101/2021.10.31.466697
- Dai D, Zhu J, Sun C, et al. GMrepo v2: a curated human gut microbiome database
with special focus on disease markers and cross-dataset comparison. Nucleic
acids research, 2022, 50(D1): D777-D784. https://doi.org/10.1093/nar/gkab1019
- Molinero N, Taladrid D, Zorraquín-Peña I, et al. Ulcerative Colitis Seems to
Imply Oral Microbiome Dysbiosis. Current Issues in Molecular Biology, 2022,
44(4): 1513-1527. https://doi.org/10.3390/cimb44040103
- Ricci F, Tandon K, Black J R, et al. Host Traits and Phylogeny Contribute to
Shaping Coral-Bacterial Symbioses[J]. Msystems, 2022, 7(2): e00044-22.
https://doi.org/10.1128/msystems.00044-22
- Chavarria K A, Saltonstall K, Vinda J, et al. Land use influences stream
bacterial communities in lowland tropical watersheds. Scientific reports,
2021, 11(1): 1-12. https://doi.org/10.1038/s41598-021-01193-7
- Lu H, Gao N L, Tong F, et al. Alterations of the Human Lung and Gut
Microbiomes in Non-Small Cell Lung Carcinomas and Distant Metastasis.
Microbiology spectrum, 2021, 9(3): e00802-21.
https://doi.org/10.1128/Spectrum.00802-21
- Ingham A C, Kielsen K, Mordhorst H, et al. Microbiota long-term dynamics and
prediction of acute graft-versus-host disease in pediatric allogeneic stem
cell transplantation[J]. Microbiome, 2021, 9(1): 1-28.
https://doi.org/10.1186/s40168-021-01100-2
- Wang R, Cao S, Bashir M E H, et al. Microbial metabolite butyrate-prodrug
polymeric micelles promote gut health and treat food allergies. bioRxiv,
2022. https://doi.org/10.1101/2022.05.01.490224
- Shanmugam G, Lee SH, Jeon J. EzMAP: Easy Microbiome Analysis Platform. BMC
bioinformatics. 2021 Dec;22(1):1-0.
https://doi.org/10.1186/s12859-021-04106-7
- Altaib H, Nakamura K, Abe M, et al. Differences in the concentration of the
fecal neurotransmitters GABA and glutamate are associated with microbial
composition among healthy human subjects. Microorganisms. 2021. Feb;9(2):378.
https://doi.org/10.3390/microorganisms9020378
- Künstner A, Aherrahrou R, Hirose M, et al. Effect of Differences in the
Microbiome of Cyp17a1-Deficient Mice on Atherosclerotic Background. Cells.
2021 Jun;10(6):1292. https://doi.org/10.3390/cells10061292
- Ingham AC, Urth TR, Sieber RN, et al. Dynamics of the human nasal microbiota
and Staphylococcus aureus CC398 carriage in pig truck drivers across one
workweek. Applied and Environmental Microbiology. 2021 Jun 30:AEM-01225.
https://doi.org/10.1128/AEM.01225-21
- Shibata T, Nakagawa M, Coleman HN, et al. Evaluation of DNA extraction
protocols from liquid-based cytology specimens for studying cervical
microbiota. Plos one 16, no. 8 2021. https://doi.org/10.1371/journal.pone.0237556
## Question
If you have any question, please file an issue on the issue tracker following
the instructions in the issue template:
Please briefly describe your problem, what output actually happened, and what
output you expect.
Please provide a minimal reproducible example. For more details on how to make
a great minimal reproducible example, see https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
and https://www.tidyverse.org/help/#reprex.
```
Brief description of the problem
# insert minimal reprducible example here
```
## Acknowledgement
We thanks all the developers of the methods integrated into our package.
- [lefse python script](https://bitbucket.org/biobakery/biobakery/wiki/lefse),
The main lefse code are translated from ***lefse python script***,
- [microbiomeViz](https://github.com/lch14forever/microbiomeViz), cladogram
visualization of lefse is modified from ***microbiomeViz***.
- [phyloseq](https://github.com/joey711/phyloseq), the main data structures used
in ***microbiomeMarker*** are from or inherit from `phyloseq-class` in package
***phyloseq***.
- [MicrobiotaProcess](https://github.com/YuLab-SMU/MicrobiotaProcess), function
`import_dada2()` and `import_qiime2()` are modified from the
`MicrobiotaProcess::import_dada2()`.
- [qiime2R](https://github.com/jbisanz/qiime2R), `import_qiime2()` are refer to
the functions in ***qiime2R***.