saezlab / MetaProViz

R-package to perform metabolomics pre-processing, differential metabolite analysis, metabolite clustering and custom visualisations.
https://saezlab.github.io/MetaProViz/
GNU General Public License v3.0
10 stars 0 forks source link

DMA function - Input_data #20

Closed ChristinaSchmidt1 closed 1 year ago

ChristinaSchmidt1 commented 1 year ago

Line 70

Separate design from the data

design <- Input_data[,1:which( colnames(Input_data)== "Outliers")]
Input_data<- Input_data[,(which(colnames(Input_data)== "Outliers")+1):length(Input_data)]

Here we may run into an issue, if the user has rearranged the DF or has not performed pre-processing using our function. Hence, we should use two inputs as done before: the data matrix (only numeric columns and the identifier, and the design information file.

dprymidis commented 1 year ago

Ok, I did this with the logic that the user can input the preprocessing output in DMA without doing much. To be sure, the above code will be something done by the user to split the processed data before putting them into the DMA function?

ChristinaSchmidt1 commented 1 year ago

Yes, this must be done by the user, but in the end the user could also just do: Input= Input[,c(1,7:144)], Design=Input[,1:7]

here column 1 would inlcude the SampleID. since we write a vignette I thought it would be the safer option and less error proned if someone has already gotten processed data from a facility and just wants to use our downstream pipeline. Would that makes sense?

FYI: I am just working in the DMA file, so I will let you knwo once I have pushed my changes.

dprymidis commented 1 year ago

Yes, there would be an issue if someone used only the DMA function.

ChristinaSchmidt1 commented 1 year ago

Ok, then let's change it to make it more versatile.

FYI: I have pushed for today and will continue tomorrow to work on the issues assigned to me.

dprymidis commented 1 year ago

I readded the Experimental_design argument in DMA and in Visualization.

ChristinaSchmidt1 commented 1 year ago

Great, you are super fast! Thanks :)