Citation:
Lakin, S.M., Dean, C., Noyes, N.R., Dettenwanger, A., Spencer Ross, A., Doster, E., Rovira, P., Abdo, Z., Jones, K.L., Ruiz, J., Belk, K.E., Morley, P.S., Boucher, C. (2017) MEGARes: an antimicrobial database for high throughput sequencing. Nucleic Acids Res., 45. DOI: 10.1093/nar/gkw1009
The AMR++ suite of tools was developed to enable intuitive processing of metagenomic data surrounding the antimicrobial resistome and microbiome. AMR++ Nextflow is the bioinformatics command-line tool for processing next-generation sequencing files into analytic matrices. The analytic matrices produced by AMR++ Nextflow are used as input into AMR++ Shiny. Within AMR++ Shiny, you can explore your data visually and produce graphical and statistical output to streamline your metagenomic sequencing project. Follow the steps below to get started.
AMR++ Shiny is available for free on shinyapps.io. With shinyapps.io, no installation is necessary, and you can begin processing your data immediately.
If you wish to process data locally, you can download this repository, execute the Install_Prerequisite_Packages.R script, open the server.R file in RStudio, select the arrow on the top bar next to "Run App", select "Run External", then click the "Run App" button to launch AMR++ Shiny in your internet browser. It is important that you run the App externally, since it will not work if run natively in RStudio.
If you do not wish to use the automatic install script, you can download the following packages yourself in R:
- shiny
- shinydashboard
- data.table
- ggplot2
- vegan
- metagenomeseq
It is important that you have installed up-to-date packages and are running an R version > 3.0.0.
AMR++ Shiny has instructions built into the App describing each step. You will need the following files that are output from the AMR++ Nextflow pipeline (NOTE: the MEGARes annotation file must match the version of the file used in the AMR++ Nextflow pipeline):
Resistome analysis alone:
- amr_analytic_matrix.csv
- megares_annotations_vX.XX.csv
- YourProjectMetadataFile.csv
Microbiome analysis alone:
- kraken_analytic_matrix.csv
- YourProjectMetadataFile.csv
Resistome and Microbiome analyses:
- amr_analytic_matrix.csv
- megares_annotations_vX.XX.csv
- kraken_analytic_matrix.csv
- YourProjectMetadataFile.csv
The metadata file format must be a comma-separated value (.csv) format file. It can contain as many columns as you'd like, however the first column must contain sample IDs that match the sample IDs in the other files. An example of columns might be the following:
- SampleID
- LocationOfSampleCollection
- SampleType
- CollectedBy
- etc.
An example of the first few lines of a metadata file might be the following:
SampleID,LocationOfSampleCollection,SampleType,CollectedBy
Sample1,Area1,Soil,StaffMember1
Sample2,Area1,Soil,StaffMember1
Sample3,Area2,Water,SaffMember2
You'll then have the choice of including each of these column features in your analyses.
AMR++ Shiny outputs the following files for every analysis:
Exploratory Analysis Files
For each feature selected for inclusion in the analysis, the following exploratory graphs are created for each level (AMR: Class, Mechanism, Group, Gene; Microbiome: Kingdom, Phylum, Class, Order, Family, Genus, Species):
- Alpha rarefaction barplots
- Heatmaps
- Barplots
- Principal Components Analysis (first two eigenvectors)
- Non-parametric Multidimensional Scaling (two dimensions) using Bray-Curtis distance
Statistical Analysis Files
For each analysis set up on the final screen, the following statistical features are produced for each level as listed above:
- Method: Zero-inflated Gaussian Regression using expectation maximization with metagenomeSeq
- Log-fold change
- p-value
- Adjusted p-value
- Average expression
- Contrast
Bugs can be reported on this github page under the "Issues" tab. Please include context of what you were doing at the time of crash and an error if provided.
General use and feature requests can be submitted on the AMR++ Suite user's Google groups page.