https://github.com/cckeneally/microbiomeutilities

The is mostly a wrapper tool using phyloseq and microbiome R packages - modified format_to_besthit

https://github.com/cckeneally/microbiomeutilities

Repository

The is mostly a wrapper tool using phyloseq and microbiome R packages - modified format_to_besthit

https://github.com/cckeneally/microbiomeutilities/blob/master/

![R-CMD-check](https://github.com/microsud/microbiomeutilities/workflows/R-CMD-check/badge.svg)   

**NOTE** While we continue to maintain this R package, the development has been discontinued as we have shifted to supporting methods development based on the new TreeSummarizedExperiment data container, which provides added capabilities for multi-omics data analysis. Check the [miaverse](https://microbiome.github.io/) project for details.  

# About  
The `microbiomeutilities` R package is part of the [microbiome-verse](https://github.com/microbiome) tools that provides additional data handling and visualization support for the [microbiome R/BioC package](https://microbiome.github.io/tutorials/)   

Philosophy: "*Seemingly simple tasks for experienced R users can always be further simplified for novice users*"  

[Package website and online documentation](https://microsud.github.io/microbiomeutilities/)  
 
## Install microbiomeutilities    

```
install.packages("devtools")
devtools::install_github("microsud/microbiomeutilities")

```  
**Citation:**   

  o Leo Lahti, Sudarshan Shetty et al. (2017-2020). Tools for microbiome analysis in R. Version 2.1.28. URL: http://microbiome.github.com/microbiome      
  o Sudarshan A. Shetty, & Leo Lahti. (2020, October). `microbiomeutilities`: Utilities for Microbiome Analytics.   
  
  
The microbiome R package relies on the independently developed   
o [phyloseq](https://github.com/joey711/phyloseq) package and data structures for R-based microbiome analysis  developed by Paul McMurdie and Susan Holmes.  
o [ggplot2](http://ggplot2.org/) H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.  
o [tidyverse packages](https://www.tidyverse.org/).  

**Microbiome package website with step-wise tutorials**:  
URL: [http://microbiome.github.com/microbiome](http://microbiome.github.com/microbiome).  

**Tutorials**  
* [Microbiome R package tutorials](http://microbiome.github.io/microbiome/)  
* [Open and reproducible spring school 2018](https://mibwurrepo.github.io/Microbial-bioinformatics-introductory-course-Material-2018/introduction.html)   
* [Tools Microbiome Anlaysis](https://microsud.github.io/Tools-Microbiome-Analysis/)   
 
### About the Author   
* [Web CV](https://microsud.github.io/gutmicrobe_webpage.io/)  
* [twitter](https://twitter.com/gutmicrobe)   
* [googlescholar](https://scholar.google.nl/citations?hl=en&user=Vahc6LUAAAAJ&view_op=list_works&sortby=pubdate)  
* [ORCID ID: 0000-0001-7280-9915](http://orcid.org/0000-0001-7280-9915)   


**MicrobiomeHD**   
The package provides access to a subset of studies included in the [MicrobiomeHD](https://zenodo.org/record/840333#.WuYuDoiFM2w) database from Duvallet et al 2017: [Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nature communications](https://www.nature.com/articles/s41467-017-01973-8). These datasets are converted to phyloseq objects and can be directly used in R environment.  

### Datasets from:  
* Duvallet, Claire, et al. "Meta-analysis of gut microbiome studies identifies disease-specific and shared responses." Nature communications 8.1 (2017): 1784.   
* Son, J. et al. Comparison of fecal microbiota in children with autism spectrum disorders and neurotypical siblings in the simons simplex collection. PLoS ONE 10, e0137725 (2015).  
* Kang, D. W. et al. Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children.PLoS ONE8, e68322 (2013).  
* Schubert, A. M. et al. Microbiome data distinguish patients with clostridium difficile infection and non-c. difficile-associated diarrhea from healthy controls. mBio 5, e0102114e0102114 (2014).  
* Youngster, I. et al. Fecal microbiota transplant for relapsing clostridium difficile infection using a frozen inoculum from unrelated donors: a randomized, open-label, controlled pilot study. Clin. Infect. Dis. 58, 15151522 (2014).  
* Baxter, N. T., Ruffin, M. T., Rogers, M. A. & Schloss, P. D. Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. Genome Med. 8, 37 (2016).  
* Zackular, Joseph P., et al. "The gut microbiome modulates colon tumorigenesis." MBio 4.6 (2013): e00692-13.
* Zeller, G. et al. Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol. Syst. Biol. 10, 766766 (2014).
* Singh, P. et al. Intestinal microbial communities associated with acute enteric infections and disease recovery.Microbiome3, 45 (2015).  
* Noguera-Julian, M. et al. Gut microbiota linked to sexual preference and hiv infection. EBioMedicine 5, 135146 (2016).
Dinh, D. M. et al. Intestinal microbiota, microbial translocation, and systemic inflammation in chronic HIV infection. J. Infect. Dis. 211, 1927 (2014).  
* Lozupone, C. A. et al. Alterations in the gut microbiota associated with hiv-1 infection. Cell Host Microbe 14, 329339 (2013).
* Gevers, D. et al. The treatment-naive microbiome in new-onset crohns disease. Cell Host Microbe 15, 382392 (2014).
* Zhang, Z. et al Large-scale survey of gut microbiota associated with MHE via 16s rRNA-based pyrosequencing. Am. J. Gastroenterol. 108, 16011611 (2013).  
* Wong, J. M. W., Souza, R. De, Kendall, C. W. C., Emam, A. & Jenkins, D. J. A. Colonic health: fermentation and short chain fatty acids. J. Clin. Gastroenterol. 40, 235243 (2006).  
* Ross, M. C. et al. 16s gut community of the cameron county hispanic cohort. Microbiome 3, 7 (2015).
* Zupancic, M. L. et al. Analysis of the gut microbiota in the old order Amish and its relation to the metabolic syndrome. PLoS ONE 7, e43052 (2012).  
* Scher, J. U. et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2, e01202 (2013).  
* Alkanani, A. K. et al. Alterations in intestinal microbiota correlate with susceptibility to type 1 diabetes. Diabetes 64, 35103520 (2015).  
* Scheperjans, F. et al Gut microbiota are related to parkinsons disease and clinical phenotype. Mov. Disord. 30, 350358 (2014).

**NOTE:**  
The aim of this package is not to replace any of the other tools mentioned on this site.  
## Change log  

CHANGES IN VERSION 1.00.16 (2021-04-14)   
  o Fix `format_to_besthit` to return all slots present in input.   
  
CHANGES IN VERSION 1.00.15 (2021-01-21)   
  o Fix `plot_taxa_cv` to deal with taxa_are_rows==FALSE.   
  
CHANGES IN VERSION 1.00.14 (2021-01-21)   
  o Added utilities within `peak-methods`.   

CHANGES IN VERSION 1.00.12 (2021-01-18)  
  o Removed prevalence option `plot_taxa_heatmap`. 

CHANGES IN VERSION 1.00.12 (2021-01-18)    
  o Bug fix `format_to_besthit`.   
  
CHANGES IN VERSION 1.00.11 (2020-11-09)  
  o Small improvement in error handling.
  o Phyloseq slots to tibble
  o `add_refseq` for storing ASV sequences
  
CHANGES IN VERSION 1.00.10 (2020-11-02)  
  o Improve `get_group_abundances` documentation and code   

CHANGES IN VERSION 1.00.09 (2020-10-21)  
  o Added longitudinal page to website   
  o Added new function `plot_area`  
  o Added new function `plot_paired_abundances`  
  o Added new function `plot_spaghetti`   
  
CHANGES IN VERSION 1.00.08 (2020-10-17)  
  o Cosmetic updates   

CHANGES IN VERSION 1.00.07 (2020-10-15)  
  o Update to `plot_taxa_heatmap`    
  o Fixed `plot_abund_prev` options   
  o Added `plot_alpha_rcurve`   
CHANGES IN VERSION 1.00.06 (2020-10-13)  
  o Added new function dominant_taxa  
  o Removed plot_ternary due to clash between ggplot2 and ggtern    
  o Added new function find_samples_taxa    
  
CHANGES IN VERSION 1.00.05 (2020-10-11)  
  o Added new function `dominant_taxa`  
  o Added new function `get_group_abundances`    
  o removed `microbiome_pipeline`   
  
CHANGES IN VERSION 1.00.04 (2020-10-11)   
  o Added new function `plasticity`    
  o modified `theme_biome_utils`    
  
CHANGES IN VERSION 1.00.03 (2020-10-04)   
  o Added new function plot_ternary    
  o Deprecated plot_select_taxa    
  
CHANGES IN VERSION 1.00.02 (2020-10-04)   
  o Version tested with R version 4.0.2 (2020-10-04)         
  o Added new function `plot_listed_taxa`  
  o Deprecated `plot_select_taxa`  
  o Added option for half violin in boxplots     
  
CHANGES IN VERSION 1.00.01 (2020-10-03)
  o Added new function `plot_abund_prev`  
  o Added new function `simple_heatmap`  
  o Added new function `taxa_distribution`    
  o Added a custom theme `theme_biome_utils`    
  o Added `gghalves` to imports   
  o Fixed `microbiome_pipeline` report   
  
CHANGES IN VERSION 1.00.00 (2020-10-01)   
  o Version tested with R version 4.0.2 (2020-06-22)     
  o Fix typos in documentation  
  o Add prefix option to `format_to_besthit`  
  o Edited `phy_to_ldf` to speed up conversion  
  o Removed `format_phyloseq` function as it is redundant   
  o Speedup `taxa_summary` function  
  o Free up `pheatmap` option in `plot_taxa_heatmap`  
  o Updated for more info from `print_ps` output  
  o `plot_taxa_boxplot` now returns a faceted plot  
  o Added new function `plot_diversity_stats`  
  o R code styling `styler::tidyverse_style()` 
  
### References:
1. Callahan, B. J., McMurdie, P. J. & Holmes, S. P. (2017). Exact sequence variants should replace operational taxonomic units in marker gene data analysis. bioRxiv, 113597.  
2. Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A. & Holmes, S. P. (2016). DADA2: high-resolution sample inference from Illumina amplicon data. Nature methods 13, 581-583.  
3. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Pea, A. G., Goodrich, J. K. & Gordon, J. I. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature methods 7, 335-336.  
4. Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H. & Robinson, C. J. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and environmental microbiology 75, 7537-7541.  
Team, R. C. (2000). R language definition. Vienna, Austria: R foundation for statistical computing.  
 
### More useful resources:  
1. [Ben J. Callahan and Colleagues: Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses](https://f1000research.com/articles/5-1492/v2).   
2. [Comeau AM and Colleagues: Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research](http://msystems.asm.org/content/2/1/e00127-16)  
3.	MicrobiomeHD	[A standardized database of human gut microbiome studies in health and disease *Case-Control*](http://www.biorxiv.org/content/early/2017/05/08/134031)   
4.	Rhea	[A pipeline with modular R scripts](https://peerj.com/articles/2836/)  
5.	Phyloseq	[Import, share, and analyze microbiome census data using R](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0061217) 

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