Code for the anlaysis of Viral BONCAT and Viral nanoSIMS data
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README.md
boncat_activity_evaluation.Rmd
boncat_activity_functions.R
boncat_activity_model.Rmd
image_analysis.m
nanosims_analysis_counting_errors.Rmd
nanosims_analysis_fractionation.Rmd
nanosims_analysis_labeling.Rmd
nanosims_data_processing.Rmd

README.md

Supplementary Information

This repository holds the additional source code used in 1) image processing (MATLAB file image_analysis.m) and BONCAT fluorescent activity modeling (boncat_activity_model.Rmd and boncat_activity_evaluation.Rmd) as well as 2) nanoSIMS analaysis (nanosims_data_processing.Rmd, nanosims_analysis_labeling.Rmd, nanosims_analysis_fractionation.Rmd, nanosims_analysis_counting_errors.Rmd) for the following publication: Pasulka, A.L., Thamatrakoln, K., Kopf, S.H., Guan, Y., Poulos, B., Moradian, A., Sweredoski, M.J., Hess, S., Sullivan, M.B., Bidle, K., Orphan, V. J. 2018. Interrogating marine virus-host interactions and elemental transfer with BONCAT and nanoSIMS-based method. Environmental Microbiology. 20: 671-692. DOI:10.1111/1462-2920.13996

Instructions for running the RMarkdown files:

For the easiest way to run the two R Markdown (.Rmd) files that produce the figures and HTML reports, please follow the instructions below.

What is R Markdown?

R Markdown is a so-called "literate programming" format that enables easy creation of dynamic documents with the R language. HTML reports (such as those provided in the journal's SI for this publication NOTE: can we provide this to the journal?) can be generated from R Markdown files using knitr and pandoc, which can be installed automatically within RStudio, and are fully integrated into this cross-platform IDE. All software used for these reports (R, RStudio, etc.) is freely available and completely open-source.

How can I run this code?

The quickest and easiest way is to use RStudio.

  1. Download and install R for your operating system
  2. Download and install RStudio for your operating system
  3. Download a zip file of this repository and unpack it in an easy to find directory on your computer
  4. Start RStudio and select File --> New Project from the menu, select the "Existing Directory" option and browse to the repository folder from the zip file in the "Project working directory" field, then select "Create Project"
  5. Install the required libraries by running the following command in the Console in RStudio: install.packages(c("tidyverse", "knitr", "lans2r", "latex2exp")) or by installing them manually in the RStudio's Packages manager.
  6. Open any of the R Markdown (.Rmd) files in the file browser.
  7. To generate the HTML report ("knit HTML"), select File --> Knit from the menu. The HTML report will be displayed upon successful completion (some might take a few minutes because of the complex figures) and is saved as a standalone file in the same directory. All generated figures are saved as PDFs and PNGs in the plot/ sub-directory.

Instructions for running Matlab Code

  1. Download a zip file of this repository and unpack it in an easy to find directory on your computer
  2. Open the .m file in the Matlab Editor.
  3. This code is currently meant to be run line by line so users can identify each step and modify code as needed.
  4. Navigate to Image directory to run code. Image names must match the users images of interest. Example images are provided as means to explore the code.
  5. Generated viral ROI fluoresence data will be saved in Image directory.

What can I do with this code?

We hope that this code, or any part of it, might prove useful to other members of the scientific community interested in the subject matter. All code is completely open-access and can be modified and repurposed in every way. If significant portions are reused in a scientific publication, please consider citing our work. Please make sure to cite this work if re-using any of our data (anything in the data directory).

References and additional software used in data processing

The following are the different outside software packages used with links to their websites and installation instructions.

  • Mapping and ROI identification in raw NanoSIMS data: Look at NanoSIMS (Polerecky et al. 2012)
  • Processing, calibration and visualization of LANS data in R: lans2r
  • General R data and plotting tools: tidyverse
  • RMarkdown report generation: knitr

Troubleshooting notes

The R Markdown files in this repository make use of various R modules for data processing, plotting and modelling. If the knitting of an RMarkdown file fails because of a missing package, please install it manually, an error will indicate which package is missing.