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!
You can install the development version of aquaras from GitHub with:
# install.packages("devtools")
devtools::install_github("Klorator/aquaras")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.
- 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)
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).
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.
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.
# Plotting with ggplot2 here...This will probably never happen, but it would be cool.