How run NOREVA R version with input data without QC and internal standard ?

[anani-a-missinou]

Basic information

My operating system: Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz 2.21 GHz, 16.0 GB (15.8 GB usable)
My MZmine version: MZmine3.0.21-beta

What happened

"PrepareInuputFiles" and "normulticlassqcall" functions don't work, despite I successfully install all required package on R R version 4.2.0 and formatted CSV table as described in your tutorial.

sample name label _477.065_4.52 12.986_0.74 133.014_0.71 420.046_2.93 439.085_0.68
Aviso_232_CuCl2_Block2.mzXML Sample 1 3.12E-01 1.77E-01 1.05E-01 1.25E-01 1.11E-02
Aviso_233_CuCl2_Block2.mzXML Sample 1 2.70E-01 1.58E-01 1.10E-01 1.43E-01 1.65E-02
Aviso_280_CuCl2_Block3.mzXML Sample 1 2.59E-01 1.92E-01 1.19E-01 1.67E-01 2.27E-02
Chifu_187_CuCl2_Block1.mzXML Sample 2 4.22E-01 2.66E-01 1.02E-01 1.21E-02 1.49E-02
Chifu_231_CuCl2_Block2.mzXML Sample 2 3.94E-01 1.77E-01 1.38E-01 4.83E-02 2.50E-02

Thank you for your help
Anani

[GCS-ZHN]

Could you please submit Rstudio's detail log information? @JianboFu0406 and @YingZhang0811

[JianboFu0406]

1. Your metabolomic data type is "input data without QC and internal standard", as you mentioned in the title. Therefore, you should use the function "normulticlassnoall".
2. In addition to input data, you have to make sure that the matrix should be numeric. For example, 3.12E-01 should be 0.312.

Please let me know if you need something else. (Alternate email address: [email protected])

[anani-a-missinou]

Hi dear GCS-ZHN,

sorry for late , I was in Summer Break.

See bellow the details of R session

R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)

Thanks

[anani-a-missinou]

Hi dear JianboFu0406,

Right, I tested this code but its don't work
multi_No_qcs_data <- PrepareInuputFiles(dataformat = 2, rawdata ="Brassinet_Roots_Quant_Dec 2021_v5_noreva.csv")
table_normalization <- normulticlassnoall(fileName = multi_No_qcs_data, SAalpha="Y", SAbeta="Y", SAgamma="Y")
table_normalization
norvisualization(data = "OUTPUT-NOREVA-Overall.Ranking.Data.csv", cutoff = "100")

My matrice seens identical to your advice

Also when I run the scripts it automatically creates an "OUTPUT-NOREVA-Record.txt" file, in which it writes traces that I don't understand the meaning of and it does not generate any "OUTPUT-NOREVA-Overall.Ranking. Data.csv" for visualization.

Thanks

[anani-a-missinou]

Hi dear JianboFu0406,

I tested with the Multiclass_without_QCSIS.csv file. It's the same. it does not generate the OUTPUT-NOREVA-Overall.Ranking file for me. Data.csv.

Normally, everything should be able to run well on my machine, of which there are the characteristics: My operating system: Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz 2.21 GHz, 16.0 GB (15.8 GB usable) and 12 CPUs available.

Thanks

[JianboFu0406]

Hi anani-a-missinou,

You can try again with the following code. I tested the following code and it works fine. My computer system is MacBook Pro (13-inch, M1, 2020) with 8GB Memory. The output file "OUTPUT-NOREVA-Overall.Ranking.Data.csv" is generated after about 30 minutes.

the sample data "https://idrblab.org/noreva2.0/download/Multiclass_without_QCSIS.csv"

library(NOREVA)
multi_no_data <- PrepareInuputFiles(dataformat = 1, rawdata = "Multiclass_without_QCSIS.csv")
normulticlassnoall(fileName = multi_no_data, SAalpha="Y", SAbeta="Y", SAgamma="Y")

If the sample data runs fine and produces the result "OUTPUT-NOREVA-Overall.Ranking.Data.csv". Then you can run with your data.

Please let me know if you have any questions. (Alternate email address: [[email protected]])

[anani-a-missinou]

Hi JianboFu0406,

I followed your instructions. it tells me that NOREV, however, very strangely it does not generate the "OUTPUT-NOREVA-Overall.Ranking.Data.csv" file.

I specify that it happened in a fraction of a minute and afterward I did not have the impression that anything was turning, I even had to wait for almost 1 hour, but nothing happened.

Thanks