/MSOrganiser

A standalone Windows executable software that extracts and organizes MRM transition names data in a few button clicks.

Primary LanguagePythonMIT LicenseMIT

MSOrganiser

License: MIT Maintainer: JauntyJJS Python

MSOrganiser is created to provide users a convenient way to extract and organise MRM transition names data exported from mass spectrometry software into an Excel or csv file in a few button clicks.

With the addition of the MSTemplate_Creator, the software is also able to normalize the peak area with respect to the internal standard’s peak area and calculate the concentration of the analytes.


AboutMSOrganiser

Table of Content

Meta

  • We welcome contributions including bug reports. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
  • License: MIT
  • Think MSOrganiser is useful? Let others discover it, by telling them in person, via Twitter Tweet or a blog post. Do use the 🙌 Show and tell under the GitHub Discussions and give this repository a star as well.

GitHubStar

  • If you wish to acknowledge the use of this software in a journal paper, please include the version number. For reproducibility, it is advisable to use the software from the Releases section in GitHub rather than from the main branch.
  • To date, the software is only able to take in the following files exported from the following software.
  • Refer to the NEWS.md file to see what is being worked on as well as update to changes between back to back versions.

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Overview

For an overview on how the tool works, take a look at the Summary file in the documentation page. Below is a preview of the Summary file.

SummaryCheatSheet

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Starting Up

Go to the Releases section in GitHub.

GitHubRelease

Download the zip folder. Unzip the folder, double click on the file MSOrganiser.exe to start

FindMSOrganiser OpenMSOrganiser

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Extracting Area And RT

The test csv data file is exported via Agilent MassHunter Quantitative Analysis in wide table form.

WideTableForm

Fill in the Required Input section such as the MS_Files, MS_FileType and Output_Directory.

RequiredInput

Next, under the Output_Options click on Area and RT

OutputOptionsArea

Click on Start and let the program run

ProgramRun

Results files are as follows

ResultsAreaRTFiles

ResultsArea

ResultsRT

ResultsAreaRTPDF

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Calculating Normalised Area And Concentration

The normalised area is calculated as follows:

NormAreaCalculation

The concentration value is calculated as follows:

ConcentrationCalculation

To do this, a corresponding annotation file is required.

The content in the annotation file are as follows:

Annotation

In the Data_extraction section, click on normArea by ISTD and normConc by ISTD. Load the annotation file onto Annot_File and press Start to let the program run.

OutputOptions_normArea_and_normConc

When the program has finished running, the results will contain the following sheets including the normalised area and concentration.

ResultsTransitionAnnot

ResultsnormArea

ResultsSampleAnnot

ResultsnormConc

ResultsnormAreaPDF

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Output Format

The results are output as an Excel file. User can change the output type to as follows

OutputFormat

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Transpose Output

By default, the results are represented in a wide table form with Sample Name as the first columns followed by the Transitions. To make the Transition Name as the first column followed by the Sample Names, go to the Output Settings section and change the Transpose_Results from False to True and click Start

TransposeSettings

The results file will now look like this

TransposeSettings

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Long Table Output

There is also an option to output the results in the form of a long table.

LongTableOption

ResultsLongTable

LongTableAnnotOption

ResultsLongTableAnnot

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Concatenation Option

When there are several input data file with the same transitions but different sample names in each file, the results can be concatenated by setting the Concatenate settings to Concatenate along Sample Name (rows)

ConcatenateRowOption

When there are several input data file with the same sample name but different transitions in each file, the results can be concatenated by setting the Concatenate settings to Concatenate along Transition Name (columns)

Concatenated results are as follows

ResultsConcatenateRow Back to top

Allow Normalisation With Multiple ISTD

By default, the software will only allow one transition to be normalised by one ISTD. However, during method development, there may be a need for one transition to be normalised by multiple ISTD to see which one is the best one to use. To relax this restriction, ensure that Allow_Multiple_ISTD is set to True

MultipleISTDOption

In this example, the following annotation file will be used

AnnotationMultipleISTD

Load the annotation file onto Annot_File and press Start

OutputOptions_normArea_and_normConc_MultipleISTD

The main changes in the results are as follows

ResultsnormAreaMultipleISTD

ResultsnormConcMultipleISTD

The output can be transposed to make it suited to be read by a statistical software.

TransposeSettings

Here are the transposed output

ResultsnormAreaMultipleISTDTranspose

ResultsnormConcMultipleISTDTranspose

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Testing Mode

MSOrganiser by default turns positive and negative infinity to missing values. However, it is challenging to trace back the reason behind a missing value in the concentration because of many possibilities.

Below are a list of possible reasons.

  • The peak area of the transition is a missing value.
  • The peak area of the internal standard is a missing value or zero.
  • The sample amount of the sample is a missing value or zero.
  • The volume of the internal standard mixture is a missing value.
  • The concentration of the internal standard is a missing value.

It is harder when there is a need to explain how the concentration values are calculated to a collaborator who is unfamiliar with your work. More so when explaining the reason behind the missing values.

The testing mode when activated will provide additional sheets in Excel or csv files such as ISTD_Area, ISTD_Conc and ISTD_to_Samp_Amt_Ratio to assist in the explanation.

TestingMode

ResultsISTD_Area

ResultsISTD_Conc

ResultsISTD_to_Samp_Amt_Ratio

It is easier to explain how the values in ISTD_Area, ISTD_Conc and ISTD_to_Samp_Amt_Ratio are created. With these additional info, we can simply tell others that the concentration values is calculated as follows:

  • normArea by ISTD = (Area / ISTD_Area)

  • normConc by ISTD = (Area / ISTD_Area) * ISTD_to_Samp_Amt_Ratio * ISTD_Conc

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