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Tools for working with MassLynx; Random assigning to groups;

Home Page: https://klorator.github.io/aquaras/

License: GNU General Public License v3.0

R 100.00%
lc-ms-data r masslynx randomization fic fu-feces

aquaras's Introduction

aquaras

Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. R-CMD-check

I created aquaras to solve some specific tasks and have added/will add more functionality as the need arises. I would never have been able to make things work without all the amazing people who create and maintain the packages I’ve used. Thank you!

Installation

You can install the development version of aquaras from GitHub with:

# install.packages("devtools")
devtools::install_github("Klorator/aquaras")

Runlists for MassLynx

Create runlists for use with MassLynx (Waters LC/MS software) and facilitate some of the data processing steps with the MassLynx complete summary output file.

Workflow summary

  • Call ras.RunlistGenerator()
  • Input all the runlist info under “Well input”
    • Optionally: download/upload the tsv under “Full list” to save/resume a project
  • Generate a runlist under “Runlist” and download the tsv
  • Do experiments. Yeay!
  • Call ras.SplitOutput() and select the MassLynx complete summary output file (the file-selection window might be hiding behind RStudio)
  • Analyze the results for each compound
  • Publish paper!
  • Design new experiments (rinse and repeat)

Random group generator

Created the function ras.Randomizer() to distribute a list of observations/compounds into groups randomly. Can create multiple series and write to excel file (not default).

TPA tools

Created the function ras.TPA_calcFromIntensity() which calculates TPA from the intensity columns. It uses the raw output file from MaxQuant.

A few more functions, mainly ras.TPAer for calculating averages and standard deviation of TPA columns.

Fic workflow

Look at ras.Fic_workflow()

df_Fic <- ras.Fic_workflow()

…and ras.Fu_feces_workflow()

df_FuFeces <- ras.Fu_feces_workflow()

See the help page for the arguments. You probably want to adapt some to your data.

Planned features

Plotting of graphs
# Plotting with ggplot2 here...
Submitting to CRAN

This will probably never happen, but it would be cool.

aquaras's People

Contributors

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Stargazers

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Watchers

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aquaras's Issues

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